{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import warnings\n",
    "from mpl_finance import candlestick_ochl\n",
    "import statsmodels.tsa.stattools as ts\n",
    "from statsmodels.tsa.stattools import coint\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = pd.read_csv('cu1901.csv')\n",
    "df2 = pd.read_csv('cu1902.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'df1' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-1-b00abbab12e3>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mdf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdf1\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmerge\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdf2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mhow\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'outer'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mon\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'datetime'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m: name 'df1' is not defined"
     ]
    }
   ],
   "source": [
    "df = df1.merge(df2, how='outer', on='datetime')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'df' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-2-c64f9f573c18>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdropna\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minplace\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m: name 'df' is not defined"
     ]
    }
   ],
   "source": [
    "df.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1826    2018-02-13 00:00:00.000000000\n",
       "1827    2018-02-13 00:05:00.000000000\n",
       "1828    2018-02-13 00:10:00.000000000\n",
       "1829    2018-02-13 00:15:00.000000000\n",
       "1830    2018-02-13 00:20:00.000000000\n",
       "                    ...              \n",
       "1914    2018-02-13 23:35:00.000000000\n",
       "1915    2018-02-13 23:40:00.000000000\n",
       "1916    2018-02-13 23:45:00.000000000\n",
       "1917    2018-02-13 23:50:00.000000000\n",
       "1918    2018-02-13 23:55:00.000000000\n",
       "Name: datetime, Length: 93, dtype: object"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['datetime'].iloc[71:164]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>datetime</th>\n",
       "      <th>SHFE.cu1901.open</th>\n",
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       "      <th>SHFE.cu1901.close</th>\n",
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       "      <th>SHFE.cu1901.open_oi</th>\n",
       "      <th>SHFE.cu1901.close_oi</th>\n",
       "      <th>SHFE.cu1902.open</th>\n",
       "      <th>SHFE.cu1902.high</th>\n",
       "      <th>SHFE.cu1902.low</th>\n",
       "      <th>SHFE.cu1902.close</th>\n",
       "      <th>SHFE.cu1902.volume</th>\n",
       "      <th>SHFE.cu1902.open_oi</th>\n",
       "      <th>SHFE.cu1902.close_oi</th>\n",
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       "      <td>52950.0</td>\n",
       "      <td>52950.0</td>\n",
       "      <td>52950.0</td>\n",
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       "      <td>46980.0</td>\n",
       "      <td>47000.0</td>\n",
       "      <td>208.0</td>\n",
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       "      <td>46940.0</td>\n",
       "      <td>46940.0</td>\n",
       "      <td>46940.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>1075.0</td>\n",
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       "      <td>46980.0</td>\n",
       "      <td>186.0</td>\n",
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       "      <td>46940.0</td>\n",
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       "      <td>46990.0</td>\n",
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       "      <td>55755.0</td>\n",
       "      <td>55677.0</td>\n",
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       "<p>20438 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            datetime  SHFE.cu1901.open  SHFE.cu1901.high  \\\n",
       "1755   2018-02-12 09:50:00.000000000           52950.0           52950.0   \n",
       "1756   2018-02-12 09:55:00.000000000           52950.0           52950.0   \n",
       "1757   2018-02-12 10:00:00.000000000           52950.0           52950.0   \n",
       "1758   2018-02-12 10:05:00.000000000           52950.0           52950.0   \n",
       "1759   2018-02-12 10:10:00.000000000           52950.0           52950.0   \n",
       "...                              ...               ...               ...   \n",
       "22188  2019-01-15 14:35:00.000000000           46940.0           46940.0   \n",
       "22189  2019-01-15 14:40:00.000000000           46940.0           46940.0   \n",
       "22190  2019-01-15 14:45:00.000000000           46940.0           46940.0   \n",
       "22191  2019-01-15 14:50:00.000000000           46940.0           46940.0   \n",
       "22192  2019-01-15 14:55:00.000000000           46940.0           46940.0   \n",
       "\n",
       "       SHFE.cu1901.low  SHFE.cu1901.close  SHFE.cu1901.volume  \\\n",
       "1755           52950.0            52950.0                 0.0   \n",
       "1756           52950.0            52950.0                 0.0   \n",
       "1757           52950.0            52950.0                 0.0   \n",
       "1758           52950.0            52950.0                 0.0   \n",
       "1759           52950.0            52950.0                 0.0   \n",
       "...                ...                ...                 ...   \n",
       "22188          46940.0            46940.0                 5.0   \n",
       "22189          46940.0            46940.0                 0.0   \n",
       "22190          46940.0            46940.0                 0.0   \n",
       "22191          46940.0            46940.0                 0.0   \n",
       "22192          46940.0            46940.0                 0.0   \n",
       "\n",
       "       SHFE.cu1901.open_oi  SHFE.cu1901.close_oi  SHFE.cu1902.open  \\\n",
       "1755                 473.0                 473.0           53270.0   \n",
       "1756                 473.0                 473.0           53270.0   \n",
       "1757                 473.0                 473.0           53270.0   \n",
       "1758                 473.0                 473.0           53270.0   \n",
       "1759                 473.0                 473.0           53270.0   \n",
       "...                    ...                   ...               ...   \n",
       "22188               1075.0                1075.0           46970.0   \n",
       "22189               1075.0                1075.0           46980.0   \n",
       "22190               1075.0                1075.0           46990.0   \n",
       "22191               1075.0                1075.0           47000.0   \n",
       "22192               1075.0                1075.0           46980.0   \n",
       "\n",
       "       SHFE.cu1902.high  SHFE.cu1902.low  SHFE.cu1902.close  \\\n",
       "1755            53270.0          53270.0            53270.0   \n",
       "1756            53270.0          53270.0            53270.0   \n",
       "1757            53270.0          53270.0            53270.0   \n",
       "1758            53270.0          53270.0            53270.0   \n",
       "1759            53270.0          53270.0            53270.0   \n",
       "...                 ...              ...                ...   \n",
       "22188           47000.0          46970.0            46980.0   \n",
       "22189           47010.0          46970.0            46990.0   \n",
       "22190           47000.0          46980.0            47000.0   \n",
       "22191           47000.0          46980.0            46980.0   \n",
       "22192           47000.0          46970.0            46990.0   \n",
       "\n",
       "       SHFE.cu1902.volume  SHFE.cu1902.open_oi  SHFE.cu1902.close_oi  \n",
       "1755                  1.0                  0.0                   1.0  \n",
       "1756                  0.0                  1.0                   1.0  \n",
       "1757                  0.0                  1.0                   1.0  \n",
       "1758                  0.0                  1.0                   1.0  \n",
       "1759                  0.0                  1.0                   1.0  \n",
       "...                   ...                  ...                   ...  \n",
       "22188               499.0              55823.0               55874.0  \n",
       "22189               877.0              55874.0               55762.0  \n",
       "22190               208.0              55762.0               55806.0  \n",
       "22191               186.0              55806.0               55755.0  \n",
       "22192               732.0              55755.0               55677.0  \n",
       "\n",
       "[20438 rows x 15 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1cf17ff8d30>]"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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VUkoVBg3EgnCu+RjNxz2jQZWwzvv4uh4ApBxMZcxXyzh+OqNIBSp5cX6n+l5JbxPHTuKub1cw4rV5UayVt/RMq8t077E0Ppy/tUAeI9KVHQJxJRXWGbZKKVU0aCAWxLtzrEzvl3RtyM9j+hTa477y99ylKCiXEOv1Qd3h8el0fnJGflUrKupUtq6nQpnYgIPLdx097Z7UEG3OiRMFNf7K1a2YF65q/lLCWk2VUqq40kAsiBNpmVQqG8dLl3WikyOLfUFrWK08Y4e3ydW5zgzsTsYYuj/9K98W0bUom9Ws4HV75fYj/LH5AHuPWdfzxcLg9W7zyFRaPzyFj38vmFaocGVlRzaJIDMrm33HTkd0Tn5k1FdKKVW0aCAWxIHj6fnSApEbvmtP5oUxhsxsw4ETadz/w+p8u9/8ZLC6H2/p3xyAUW/9zhXvLwr7/LTMbPfYsWjJzPaeWZvT7M4Xpm2gx7MzORxgXVHwtAa69GtZM28VtJWN8wz4v+fbFSSOneROj6GUUqrwaSAWxEuXdeLLG3tG5bEjbV0JJdtAdhFP+WCMIUYgNoJ348VdGxRIXTbvP8FTv6wjM8LgJNPnNbvsvQVBj83ONoyfa80I3R+kFbOzoxV249PD+eT6HhHVJ5gYRxfqj8t3AtDyoSl8vnCbu/yP5AMkjp1E8r4TfufvORpZK55SSqnQNBAL4owGVWhSo0LOBxaA3GZQv7JnY67t3YR7h7Z2lxljcDbWTFtbsHnGXpi6nsSxkyLK95VtQIC3Zm0OedziB8/lH32bAvDjsp15qWZQD/y4mg/nb2X9nuMRnecbPC9JCT7Z44/NB93bx04FTiPhjAMT4mLyJat+KI/8tMa9fcUHVmvkoJe9Z4De8vlSej03s1jnqlNKqaJGA7EiKCGX6wA+c1EHnhh1BmMGtnAHY74tYv/8fGm+1DGQf329nLdnW8FUWgRrZRpMwPFPtw1o7nW7duWy3Du0NdPvPtud5uPTG3rQr2VNujTO+zi+3s/NZPHWQwAsD3NW4eGT6Uxatdu9FqkrjYirK3HNzqMkjp3E7A373Odc9aGn2zXY4tuu12xkh3oRXkXuuYL0YI851d7/wrT1hVYnpZQq6TQQK4JGda6f5/twdSudyshi497IWndya+LKXe7tLfsDBxiBGLtF7OGRbb3Knetyfn9LbwDKxsfSqk4lXr+8C10bV3UHPs4GuIMn0rxaqE5nZHE0SMvT/E0H6Pv8b4ybsp7djm63E6fDWwKoy1MzGPPVMm76zMr1dfcga/3PDg2qcDQ1g/PemA/AdR8vYc3Oowx4cRZxjtat+75f5XefK7cf4bf1VuD21pVdw6pHfvjn50tJHDuJSas9MyoDddFu2X+StMyiMVtVKaWKOw3EiqAycbEsfXgQSQ8PyvV9TLDH/3yxcFuhJXh1JqMd8fo89oY5K3DH4VMcPJnOjf2akTJupLv8ZsdKAt0Tq3udc2ZidX68rQ9l4mKJEcEVdp1Iy6Tb07/y0ITVDPzPbFIOnKTNI1Pp9MR0Hv15Det2HfO6n6s+XMSOw6fc6Upcnp+6nuwcxuqdbwdZrscFT7fyqYwspq3z7sI77435pBxMJTPbhJwIMuqt30M+bn65pneTHI855JhMMKx9Xfd264enkpRySJdKUkqpPNJArIiqUbFMnhJ4ulpmXpy2gQ/sBKNVysUzpF3g9S3z6rf1e71alAB6Pjszx/NcLStzNu732xcf5uh9Ec8sRVcS22+WbGfrgZMM+M9s93GfLdjGiNfnhRy/9uKlHd3bu0MEkuOmrHevRep0Mt26no9/TwnY2uXi20KXmZXN5wu3ce5LnvrOuXdA0PPzwx3ntMzxmB7PzmTH4VQSx05i3ibv1+jSdxfw4fytEU9sUEop5aGBWAnVvn5lv7L6VctxqoASoLqW4fGVU7doeoCxZO9f052nLzwj7McWYNWOo/R9/jcOn8x5DcU9doDlbLEb3K4ObetVZoRjfFSfcb/5nXvwRBrzNu33a0G789yW3D2oFX1bhJ9monJZq+s1K9swbsp6HvlpDZvtLt1RnesX2GSRyf/qx7tXdaVaeU+r3PiruwU9vu/zswBPkOnL97lQSikVvvxLWKWKlLmb/FuYqpWP52SADPUFaeeRUyHXywwUiA2OsNXONdB/x+FTYSV2zbCXI+r9nKfF7r2rurlTO7xzZVdu/XIZAKfSsyiXYOXeOngijW5P/+p3f87uVF99W9TkqQvPYKCjZc7lmD0O7aoPFrFgy0GvfT+v2MVro7vkeC250a5+Zdr5BOqD29Vh0zPDOXYqgwH/mc2E2/r4zZp0+efZzfj4jxT3a3ciTceLKaVUbmmLWAkVqPetYpk4UoO0auSX+4a19rqdlkMLnGt25QWdgk9QcLUcBeMa2A6e3Fi+Vj8+hAdHWCsWuJKvOoeAOfNrDXe0irV9dCrGGP5IPhAwCAtkxaODuaV/c/53e1++uLEnTaqX57qzEvn1nv7ugfpz7x1IaztA9Q3CAK/WqoKUMm4kKeNGIiLEx8ZQo2IZVj8+lBa1K3JDn6YBzymXEOsVQL87Z7M7ZUni2El0emJ6odRdKaVKAm0RK6Eu6trAK0knWLMQj4c5GzASxhgaVy9Ps1oVuG1AC16YusG973SGf8b5pg9MBqBB1XJ8YSfN7dOiRsD7/u6fvWlSo3ye61ipbDz1q5YDrFa6tT6D9n3dP6wNz0+10jSc98b8iGaeVi2f4LVMVUyM8PgF7QFIfnaEu/xwkEXZZ/5ff+pULhtwX2H679Lt7u0b+zZ1jzWskBD438Z/k3YA/uPflFJKBRdWi5iIpIjIahFZISJJdtmLIrJeRFaJyAQRqeo4/gERSRaRDSIy1FE+zC5LFpGxjvKmIrJIRDaJyLcikpCfF1katalbiRa1K9KpYRUAujWpRsUycew8cipgd2Be/LRiJ38dSnXn4HLyTXPgbL3aeeQUd3+7AoCtB1ID3nePptVzHZQ8el47kh4exK/39Adwt0Zd/eFi7vh6echzL+nmydy/dtcxMrI8zWe1KpXh83/kPdP9xNv7+pXFxwrNa1XM12WucusJO3gEePi8du7Ws/JlYgMe36xWdBIgK6VUcRZJ1+RAY0xnY0x3+/YM4AxjTEdgI/AAgIi0A0YD7YFhwNsiEisiscBbwHCgHXC5fSzA88ArxpiWwGHgH3m8rlKvfEIcv97Tnyt7WikKEmtUoJLdxXc6DzmgZv6512vWYXa24e5vVwK4uz2THh7EpH9ZQca0tXu9zvfNQL/CTpw6sHWtXNfp+1t68/413Xnu4g5c1r2hu7xrk2rUrFiGFrUrAsHHMtWu5D87tXalsrSpG3hs26t/78yZPuk0csN3PUmAAa1r5/l+88vFXa3n8pw23nUqn+AJxB4a4cn9dum7nmWddP1KpZQKT66/dhtjnANBFgKX2tujgG+MMWnAVhFJBlzNB8nGmC0AIvINMEpE/gTOAa6wj/kUeBx4J7d1Ux6uvFbZxpO7Kqf8WL5OZ2Tx5m/JVKuQwFO/rOP6Pok8dr7VWrLj8Cm/42tWLEO5eOvD2tkCBt55qZzKxgduZQmHM8fY5T0aM+7ijpxIz6RyWe9xVjPW+S/Nc/+wNlzUJfC6lYGWOVr04LnUqVw2oiWcgvFdTeCDa7rTq3ngLtpoCTQRIS7G8/3tprObUb9qOcZ8tczrmKOnMvKUfkUppUqLcFvEDDBdRJaKyM0B9t8ATLG3GwDbHft22GXBymsAR4wxmT7lfkTkZhFJEpGk/fv9ZwUqf23rWbPj+raoyVuzkgGYn3wgovt45deNvDkr2Z288+PfU9yzEzMcC1n+185+D1DGsUyTMYafV+xk+to97laz1y/3nhGYn9n/Y2LELwgDGHdxR6/b1/dJ5NYBzalbJbyuz1/u6OvuJhURljw0iLVPDM3hrPCMGdicQe3qFIkuyZy4XltXV2Tbev4thzpOTCmlwhPuf/0+xphdIlIbmCEi640xcwFE5CEgE/jSPjbQ6sSGwEGfCXG8f6Ex44HxAN27d897k0Qp0K5+ZVY8Opiq5RNIy8zmwQmruf2r5ZzXMfxllOZu9A/c3pqVzPV9mrLriKdFrEYFz9C+OEcy1tu+XMYUe6HoMQOt9SPb+nT7nRVB/q3cquao3/qnhkXUCheoZahWgC7N3Lr2rMR8u6+CdtoeY+haxqpZrYp+x4yfs4XnL+3oV66UUspbWC1ixphd9u99wATsrkYRuRY4D7jSePpqdgCNHKc3BHaFKD8AVBWROJ9ylU+qlrcCkG5NqrnLIulaa1DVv8XowIl0+oz7jfFzt7jLnF1W4EnB4ArCAPei4M6s+SnjRtLAntFYWBLCyNrvGiMWKk9YXv2jr5UiIthMxKLo/I71OK9jPebfPzDoMd8mbQ+6TymllEeOn0YiUkFEKrm2gSHAGhEZBtwPXGCMcU55mwiMFpEyItIUaAksBpYALe0ZkglYA/on2gHcLDxjzK4Ffs6fy1NOTWt6ZrW9E0E29F//3BewfOeRU8zbZLWWXd6jEY2qewdTh1P9u6dc8Z+rdcqZ5qEwOfOGBfPNzb2Y9e8BBVqPB0e0ZeWjQ7wWOC/qRIQ3r+hKw2r+aUVcM1TrVi4b8VhEpZQqjcL5718HmGAPLI4DvjLGTLUH4ZfB6qoEWGiMucUYs1ZEvgPWYXVZjjHGZAGIyO3ANCAW+MgYs9Z+jPuBb0TkaWA58GG+XaFyS3CM23p5+kZuG9Aix3OOnQ5vrM81vRP9Bp8nxMUETZVRpVx8gbY05Yeq5RPcrYkFJTZGqFJIyVsL0qx/D6Ba+Xj387Xn2Gnu/X4VL13WKco1U0qpoi3HQMye5ej339QYE/RT3BjzDPBMgPLJwOQgj5H3xEwqbJnZhrTMLMrEhR4n9eZvyWHdX/UK/gHLz2P6MPy1ebmqnypenK2tLj8s26GBmFJK5UCXOCrFxs/ZkuMxW/afAKB/KyvP17z7BvLgiDZMvL0PX9/Uy31coKSrjap7uq4WPHCOe/vv3Rv5HVtYfLtPlVJKqWgqPgNTVL5L2nY45P7fkw9QpZzV0vX+Nd3dXZs3n23NfDyVw7qVcY5xWPWqeAKgTo2qBjq8UEy/q797rUmllFIq2jQQK2Uu7Fyfn1ZYk1LnbNzPybTMgAPFn/5lnXttwRjxHl/mUi4hlom39wn6WGXjYxl/dTe6NK7mVT6yY70gZxS8cgmxWEMUVUH559nNeM+eTZuZle2VykQppZQ3/Q9ZyjxyXjuv27uPng54nCsIAwg1+a1jw6p0bBi8hWtI+7rufFs/jenDi5d2dGf4VyXTAyPa0qOptdpBps6cVEqpkDQQK2Vq+Cw7U6FMLF8u2kbi2EkFvj5g50ZV+VsUx4epwjO4bR0A0nXNSaWUCkkDsVLotdGdqWqnTIgR4bnJ6wFItRfF9h379fOY4N2PSgUSH2uND8zM0hYxpZQKRQOxUmhU5wY8OKItAOmZ2ZxIs5b5PPOZX3l84loOpVoLc/+zfzNSxo2M6uB6VTy5xoVlaouYUkqFpIP1SynX4tLbDnoWRUjPyuaTP1LYfdRaPzJ574mo1E0Vf64WsQwdI6aUUiFpi1gpFWNnwV+ccshv37S1ewFoW69yodZJlRyudUe1RUwppULTQKyUe33mpqD77hzUshBrokqSeDvdSUFPAFFKqeJOA7FSymdZSJ656Ay/Y+I1/5PKpXg7mW+GDtZXuRRsnVqlShr9pFWAp6tSqfzgGayvgZiK3PS1e2j18BRW7zga7aooVeA0ECulUtMzvW7HiLWOpMsn159Z2FVSJUice7C+tmqoyH2zZDsA578532/f1DW72X4o1a9cqeJKA7FS6sRp70BMEK9Fuvu1rFXYVVIlSHxM0W4R+3P3MeZu3B/taqggBrT2/P8ZPX6Bezsr23DLF8vo98IsPpi3hXdmb45G9ZTKV5q+opQ66ZO01dUzmTJuZBRqo0oaV4vYV4u2kW0MvZrViHKNPI6fzmD4a/MAfb8XVc6hEgu3eGZ2HzuV4d5+etKfAFx7VhPKJ+hHWSSS9x1n0Mtz+fWe/rSoXTHa1Sn1tEWslDqZ5t0iZopmw4Uqplx5xH5asYvR4xd67Tt+OoPJq3cXeGugxXEAACAASURBVB2Onsrg2cl/kpaZRXpmNp8v3EZmVjaDXp7jPiZb85wVScFm2z4/db1f2eszk3O8v91HT/HS9A36etsmr94DwM8rdka5Jgo0ECu10nxmJGn2fJWfXHnEXJwfgB0en85tXy4jKUAOu/x0y+dLGT93C7d8vpTPF27jkZ/W0OKhKew9luY+5o5vlru3l247ROLYSWw9cLJA66VyFqxL2zV2zKld/ZzzHT40YQ1v/JbMkgJ+zxUX5RNiAdhx+FSUa6JAA7FSKy3D0zX50t860bpupSjWRpU0rq5Jl0CD9i99dwEfzNtSYHVYsOUgALM27Gfmn3sDHjNpladl7pJ3rLFIv6zcVWB1UuH5YdkOAC7sXJ86lcuEPPZfXy8PuR/gt/X7APjJbgE6fjqDxLGTuP7jxQCs3nGUpdsO56XKxUqlslZX7oTlO/16R1Th00CslLqxXzNa1q7Inee25KIuDaJdHVXCHDvl/c/d1cLx10Hv2W6ucT4F7Y/NB0Pun71hn3v7pRkbC7o6pdL7c7eQOHYSr8zYyIm0TI6mZgQ9dv2e4wBkG9h7LI30zGxeCNAtGY59x0+7t79ebLWozdqw3+v3+W/O55J3/oj4vg+eSPMK5ouLauUT3Nv3fLciijVREGYgJiIpIrJaRFaISJJdVl1EZojIJvt3NbtcROR1EUkWkVUi0tVxP9fax28SkWsd5d3s+0+2z9WkVgWsUfXyzLinP3cPbkVMjD7dKn/tP5HmddsViE1ft8fvWN/grLAt2nKQ6z5e4lW260hkXTbGGDo8Po0Z6wK3vCl4ZrIVdL82cxMjXptHpyenBzxuy37PGrcT7dbJVg9P4W3HDMnLujcMeO7jE9ey2XH+b+v3cvHb3gHWKzM2csqRvue0o3cgO9uwfs8xDp1MZ++x04SScuAk3Z7+lTFfLePQyfSQxxY1ZeNj3duuJe1U9ETSIjbQGNPZGNPdvj0WmGmMaQnMtG8DDAda2j83A++AFbgBjwE9gR7AY67gzT7mZsd5w3J9RUqpqDu/Yz2v23fb37o3BVhI/oK3/HNFFbSUcSNJrGGla/m7z2QCgLPG/RbR/f3z86UcP53JTZ8l5Uv9SqKrejV2b/9l5wG73Oe5X7rtMOe8NIecPHdxR6/bh0+ms27XMT75I4VzX5rjXuP0hk+S/MZBvTZzE/f/sNp9u80jU93b2w6lMuzVeXR9agY9n51JSojxgk/+ss69nVXMJwEcLmaBZEmTl67JUcCn9vanwIWO8s+MZSFQVUTqAUOBGcaYQ8aYw8AMYJi9r7IxZoExxgCfOe5LKVUM+TZqu8botK1njUV05ok6EqKLKi/a1K1Ex4ZVvMo+uKY7f4w9B4B3rurmd047e6H7G/o0jeixpjtawly5rVyD//VDzlKzov9YL9c4PoB1u475dQ82qFou4H3FxggbnvZ8Xz94Mp1jpz3voxs+9Q+IP7imu1+Zryve9w4MQ3Wdu97TAIaCDcRyap3Lq0d+XlOg969CCzcQM8B0EVkqIjfbZXWMMbsB7N+17fIGgHNqyw67LFT5jgDlSqkS5Mn/rSPTbjl46W+dCuUx61Yuy2//1x+AcvGxDGpXh/r2h3vdymX9ju/Xsqa1r0roAeK+alXyHP/81PXsOXqaaz60BoJ3eWpGrupe0qT65C50OWB3Y/t2ZwP8/cxGfmXX90kEoExcLLXt533Qy3M47khSHShZ76B2dXKs4+6j3gHP8r/CG8C/ZGvBDfT/ecVOej47k0//SOGPzQfy5T5dYeN/7L/DNjpZK6rCDcT6GGO6YnU7jhGRs0McG2jAkclFuf8di9wsIkkikrR/v2bFVqooa1azgtftj37f6g7EysTHugMkgA324Oz8lJVtiIsVmtWqyIanh7HmiaFe+8vE+//7q17BGsScGWFXU9fG3ulfej030y9pcmnnu6yay9pdxzDGEBdgrOod57SgsyO1zttXduWx89u7bz9/iaeL0rdbuMPj09zbv9utoI+d385ddmHn+jnW+WCYrZljvloW1nGRyMjK5qlf1nHnN1a3/mMT13LF+4vy9TGa1rS65zft8x8yoApPWIGYMWaX/XsfMAFrjNdeu1sR+7ernXYH4Pwa0xDYlUN5wwDlgeox3hjT3RjTvVYtXYJHqaJswpg+/O/2vl5l46ZYM99ixQqQXIa+OjffHz8r2xBr5zMrExdLrM8HfZk4z4Dlibf34YqejbmipzWOyTeP1TUfLabv8/7jxt6ZvZnJq3dz4ES6e8xZIMn78j/QLG5S07NoULUcKeNGkjJupDvAWrPzKE0fmMyVH3iCjI+vP5OUcSMREVZsP+Iud7Y8AnRLrEYwzhYyVxfngNa13WWvju7CNb2b5FjvjXvDe+2W/3WYdbuO8fXiv8I6Pie/rNrFh/O35st9+TLuDN7W38TPKzRlSzTlGIiJSAURqeTaBoYAa4CJgGvm47XAz/b2ROAae/ZkL+Co3XU5DRgiItXsQfpDgGn2vuMi0sueLXmN476UUsVUlXLxNK1VIeA+36CoIGQZQ2yIh3HWoWPDqjx7UQcqlrHyK/m2iM3duN9r0Pehk+mcTMvk+anrue3LZRw4kUaHhlV57uIOAR/r0MmCGQdXnKSmZbkTiQK8cXkXAF6ctsHruPFXd2OgI2Byqlou3ut2OO+iGhU8qRp8c5KF0/J50Vu/h/EoVk6uEa/P44EfV+d8cBhOpoXXojr8tXn8sHRHyGO2HjjJQUfX7x67C9Y5lDNUOhFVsMJpEasDzBeRlcBiYJIxZiowDhgsIpuAwfZtgMnAFiAZeB+4DcAYcwh4Clhi/zxplwHcCnxgn7MZmJL3S1NKRVvZuMD/YgojEMvM8rSIhUtEiIsRsgIkoAVIz8zmVHoWXZ+aQfvHPF1fB46nUbNiAsEu67L3FjhaIUqfxVsPMXXtHq8uMFdSUV+NQ7QstqzjPZapUtn4IEd6XODogiyfEMe8+way+KFzAe9Ws2CD+cPtYv5swTb3dnpm4PdPTt6enUzi2EnsOXqapyetC3iMa0bo9kOp/LpuL3/uPsb//XdlyPsd+J/ZdHv6V+ZvOsDVHy5irB0slo2LZaQ9wzlYOhFV8HL8L2WM2WKM6WT/tDfGPGOXHzTGnGuMaWn/PmSXG2PMGGNMc2NMB2NMkuO+PjLGtLB/PnaUJxljzrDPud2U5v9YSpUgcbGB/8W4ApYFD1hjd/q3CjzU4L9J2/l8QUrEj3v4ZDo7j5xi1Y4jOR/sIzPb8NaszWw7eJL9x70HkL89O5mLAyT+PJmexf7jaczeEHzs6rhcJiQtCS57b4FfWVVHUlGn1j7BVuUgAZuLq6vTxTn2EGD0mY29bjeqXp7alayJGscdMy2rlreCui6Nq4a9GHy5+Fim3tXPr/zP3cdYkEMS4UBemGq1DvZ6bianMzzBXLcmni7Y03aQ1++FWdwYYbqUqz5cxLxNngH/lcvF0dwxRCAtU8c1RoNm1ldKFarYGHGnt6hXpRwdG1YhWArne79fxSM/r434MW79cimQt0HI/V+czZnP/Eri2Enusld/3cSfu48FPP6XVbvp0bQ6gHv8071DW7v3d29SPdd1KU18U5+MDyPtBFgzcV8b3dlr7OGUO/uFXL7t2ClPINa+fhXa16/MI+dZA/pv6d885ONVKRfPZd0b0qau/1qXo976ncvfX8jQV+aydNvhPCV8HdS2Dk0dE1+WbTvM/33n3wIWLJfZul2B369gpRS5bYDnOqOdXLm0Cv1VQyml8mjefQOZtnaPOyeT7weGiBCoDdy3YXz0+AUMaluHG/s1y/ExF24Jb3HnpQ8PIiPIAtORum1Ac67tnUivZjVoa+cjO5GW6R4DFR9qwFoJtseREiLp4UEhj51xt/+E/HBzaF3SzTPnq3ezGlzaraH7dQjGla7ikfPaUS4hlkn/8rRujR3ehoys7KAD5tMzs90Z6jc9M5yWD/mPqNmw97g7N9r/bu9LB5+8duF46bJOpGdm8709DuyajxYHPG7z/hO0quMfdI54fV7Q+3bVv0q5eI6eyuDlGRsD5tdTBUtbxJRSBapR9fJea9v5EiA7QCT29/c8yTX/OpjKwi2HIl6b8uazQwdtNSqWoW4V/3xi4Vj7xFA+vNbTWnPnoJbExIjXh3/FMnH8cGtvoPhnXw9HWmYWPy3fyT5H8HTklKc1KFBSV5eUcSP9xoABjOhQjx6J1f26HEP5+uZeXoFZMK5A7IJOgVNZlI2PCTqeMSMr2724fXxsDA+PbOvVAupr/Z7gLVNgLa/k6+5BrahSLp5alcrw9pVdA5wFA+3kyENeyf3MY9dzO2XNHp7+ZZ1XctxA3pm9mTd/2+S+vf1QKt8lbQ9xhgpFAzGlVIGLC9Ea5OyJmrRqNxe//TvZ2YbFKZ5WrbNfnBXW45xKz+KGT6x1I3s0rc6DI9rmrsJhqFAmjnPb1uGXO/qy9bkRXukwnFytDpHmJiuOHv1pLXd9u4Iez850lznHOgVzfpBACKwg57tbent1OeaXX+85m2t7N/FLi+ESFxNDVrbxa501xpCZbYh3jIG8sV8zhp9RN+hj3fv9qpB1OZ5mTRxoW68yM/+vP1f2bMyYgZ5uw5gA/ffjr+7GdY5VIBLHTvLqSgcryKxeIcE9lm7JQ1arpPM5r+6YWfrB/K10fHx60GAsK9vw/NT1/Gf6RjKzsknLzKLfC7O47/tVLN0WXku08qaBmFKqwMU5Zi/6ZrSPcXRNjvlqGcv+OsLCrTkPdL72o8V8+keK+/aeo6e5/P2F7qVnnItHR+Lrm3q5M7Y7PeQI6pyDuc9oUMVvXJOT69ojXUi8OHIu6u7Kbn88ROvK2ieGMvyMuoW20oKvFrUr8cSoM4Lud3UnO7uvp63dQ9MHJtv7vT9C43KYpevMSZaUYi2B5ZoQ4hqvdn2fRJrXqsgzF3Xwmuzi+xZ7/5ruDGlfl7Pt1SCcXMGYMYaJK3d5jVGrVakMKeNGutOHWPft//5dt+sYqemZJI6dxEMTPCk5nK/njZ8lMXWN5zW/5J0FnM7I8lpIXeVMAzGlVKFyzZR0CdQ1GU4G8Tkb9/PYRM9A/l7PzfRK/nngRO4GSPduXsM9YPvsVrXY9Mxw1jwxlJty6OYMxtW19cT/AqcjKCkenLCaw45cVNd8tJjEsZMCLjfkUqFMHO9c1Y2EIGlOos3VmpeVbdwBxj8/X+re7zvuz5l6I2XcSN68oovX/i8XelJcuCah/LBsB/M27affC1arb5VygVNy7PRZvHywvWRTsC8Bxpg8La9VsUwc7R61UrR8uegv1uw8CsCvf3rW2Jy9YT9Lt3kv79Tmkam0eWQqiWMnhZ0Mt7Qrmu9+pVSJ4vrA6t+qlt8HhwgBB+sHs/PIKa9v5buPngo4/qpR9cALRofDFRhWLRdPfGyMO9ErBP+gDMY5xmhOiKAktxZvPeQ1ID5avloUOKP8+/Oswe5PXNA+4P6ibPZGe7H6R6e6A4xezTyzX3cd8X/e598/kKX2pARXd6Jr1YVJq3ezascRjDE0qma9P+du3M/VH3oG4FcOkhvN+Q6/e1CrHOv+zpzNNKkePCebr/M71adGhQT30mTnvTHfa/8/Pl3CyzM28m+fnGXO/Gm+hrwylxNpgZe2Uh4aiCmlClzfljW5sHN9xl3in3leRDD4j8MB6JHon/Khz7jfvLKxf7FwG4t8ujIv7FyfCbf1yXV9XYGd70DtlHEjWfnYkIjuyxk0XhtkxlteXPbeAno9N5OxP6zKdSLRwhBoAe+ibvO+k35lPZrWcG+nBXi+G1YrTw17UsI2Ox1Eiv37wIl0Lnjzd+79fhULtljv2T988o0FWgMVPIlcwZoYEsjlPTzP8QtTN7hnUf73lt4Bj3d64/IuLH1kMP8OMuFg77E0Xp/pGaBfrbx3wPjDrWcFPO8MR+JjFZgGYkqpAlc+IY5XR3ehXhX/Viqra9L6Bu9rQJvAiV6d38LfmrXZL//Rq6O7hJyhl5Ouja0Emhd2aZDr+3ApyFUEnB/O3yzZzpKU6A2Wdl1nvwBjlsAzaaE46eKzmDvA0VSryzuxRnn+0Tcx5PmutSzf98mF9v3SHV5Z/V1Gn9mILo38HxM8kz2uO8v/Mf9vcCs+uKa73+zk/9opL84M8IUmGN8JB848Y04/jfF80enQoAqdQqTmKAottkWZBmJKqaiKEQGD18D7QW2ttQbP7xh8Np3T2Hxa388lsWYFUsaNDJrxPxLNaubvbL8Z6/ayef8JjqSms3LHUa990VyTxNV9e0aDKnx5Y08+uf5M974WtfN/xmNheG10F7+yT+0vAbPvHUiL2sGTxYI1Bi5l3EjObhU4OHVqVaci4y7pGHTMV2O7m7FTI/+A545zWzKoXZ2wZqjmRER48dKO7tu1KpXhTJ/F1effP5AmNSq4Z2L+746+xMXGBH2dX5q+IWC5smggppSKKhFrTFZPR5fPS3/rzLtXdaNR9fLuD4GRHepFq4p5Ui4hlpRxIzmreY2cD8aalZc4dlLAvFLT1u7hps+SOPelOXR+coY7WajLVR8uYvdRawxdQYxHC2WUvabjv4e0pk+LmgxwLNx9xzktCrUu+SVYWotIBUtt4jRmYOjn6LyO9Zhw21lc2Dl4K21+LVHkTBWyfvdx/nuLd7djsOfl3DbWa+7bivbfHBYlL+00EFNKRZXdIMbQ9laXyNS7+lGlfDzD7C6Sj647k+l3n80bl3dxL9bs1LdFzq0NRUG3JtXsiQmhm61cs/ICJch0zthzevz8du7t3s/9RofHp3PtR4vDzkqfHwRrIoOzK/Z/t/dlYOtajAoRPBR1SQ8P4v8Gt+LBEW0K9HF2HA6d3kRE6NK4WshUKRlZ/i1iPZtGvrRWV0eXrGuw/dx7B3JL/+Y8Oap90MDy/4a05qW/deLfQ1rzyt87BUwDo/xpIKaUiiorj5hxz1SM8xlTValsPK3qVCImRqhdqSzD2nvGsLSpW4myPoObe+Tig6cwlI2PxRjYcsB/AHggY39c7TUGLDPAh6xL8yBdQqPe/D2ySubgRFomo8cv4MCJNL99Bv9cVx0aVuHj63vkax0KW82KZbjj3JburkGABlUjn5E7776BfHljT85o4Fl5wZneIkR8FbZ/D23N+Z3qu1uP7xvWmm//mfNAfV8iwqx/DwDgb92tFQoa1yjP2OFtuKZ3YtDzEuJiuKRbQ2JihIu6NGTxQ54lrXL6AlKaaSCmlIqqw6npLPvrCCvtHGChvvEDZGZ7ApKEuBiO2okwXQOrHxnZLuB50eaaielcusmX74dVpyemu7e/dKSHuH9YGy7v0dh9Oz0zm2l3+a/TuOfY6XxdWqn3szNZuOUQj08MvBB7SV5N09l1Hmoh8WAaVS9PnxY1+eWOflzR03rtzutYnz+fHMZj57fj1hwWGQ9H7UpleePyLu6VLHyTJ0eiqT1O0tnFnBcvTd+YL/dTEmkgppSKqjU7rTX4PrAXV47NIRBb/pcnaevBE+ksSbESSvZsWoOUcSNztbByYfhzt3WdgVqTXE6mZ/nd/m39XgCcDYW3DmjOJV093X2HUzNoXbeS3+w8gP+t3JWXanvpZM/o23csQItYCW/wqFYhgXfs9R7zGnA+e1EH9+oM5RJiub5P0xy/gETiH32bUiEhln4t8z7ZJL+8OSs54nMOn0x3rzxQkmkgppQqUio4kqcGctBeruXSbg3Z6Vg26Nc/9xZovfJqimMpmGBOBEhpcMMnSSSOneTOxO6avOAcU+QaKD+4XR2/rtm7vl2R6zr7mp98AIDFKYcY8socv/35GUwURTPt5bNcv4uqjg2rsvbJYfk22SAv/nWuf86z89+Yz7gp63M8t8tTMzjzmV8LolpFigZiSqkiJae0W9/ZY17uH+Y9ePqqno0DHV5kjA4joek/PrUWLP/3kOCZ08cOt657eAfPWDnnmoe9moU3OzNSm3yWq9m49wQnHVnTDSW8SQzPxJC8dPmVNvcM9ryXf16xk8Sxk1i98yjvztnM27OTSRw7KeBsz8VbPTnxfl1XtL9k5ZUGYkqpYqVH0+qkjBvp923/vE7h5RyLlnGXdKRKuXivyQZOOw6nsnaX1X3Zpm7lgMcA7qSdZeJiufPclvxwq/dg7BoVEgKdlmc32EGiU/vHprlbJb9Y+JfX4tIl0YVdGrDowXP91ktV4bnzG+/W2RemWvnFnEGXy2XvLXBvfzB/C1nZhpQwJ7oUNxqIKaWKlBoRZMT/3+19aVO3EvPvH5inTPqFJbFmBVIz/L/9G2Po+/ws9+1z2gQeIH1Fz8ZeOZ7uHtyKbk28uyKv7NmYcRd34O0ru9KsVoV8qjlsPxQ4vcK2gyXzwzGYOpXLlvgu2MIWKIBv6ZgJvHDLIV6fuYkB/5nN1hIYjGkgppSKKmeXXaUcxof56tCwClPvOpuG1cJf3DiaysfHcio9k+xsQ6uHp/DZghQAbvosyeu4mAD9szf1a8qzF/mv1ekrLjaG0T0aM6JDPc5sUp2aFRMCJofNC2eLUKwIk1btztf7V6XLnd+s8JtUsmnfCa/br9nrXO4rxNx4hSXsQExEYkVkuYj8Yt8+V0SWicgKEZkvIi3s8jIi8q2IJIvIIhFJdNzHA3b5BhEZ6igfZpcli8jY/Ls8pVRRN+4Sz3IqHQMs31KSlE+IJTU9i+Xbj5Cemc2jP69l+6FUfv3TM/jbNZvOl2t2aCQS4mI4cCKdZg9OZv6mA7mut3OtwDEDm3utGTp7437GfLUs1/etFMAdXy/n5xU7czyuINdujZZIWsTuBP503H4HuNIY0xn4CnjYLv8HcNgY0wJ4BXgeQETaAaOB9sAw4G07uIsF3gKGA+2Ay+1jlVKlTElPgVC+TByp6Vnc8IlnvFWmo7Vqyp393Ns/j+nDU6Pau2+v2O5J2xGuCcs9H2xXfbgo4vNdsuwXpl29ytw71HuSxDuz/RdrVyonyx4ZzIpHB3uV3fnNCowxXrOhfVcGSM/M+3qaRU1YgZiINARGAh84ig3gGlFaBXC1K44CPrW3vwfOFatDfRTwjTEmzRizFUgGetg/ycaYLcaYdOAb+1ilVClzYZfiuxROOMrHx7L1wEl3Elqw1o90qe/I2N6pUVWu7p1ImTjr33RuVgw4keadDiO32c1dXZvX90l0l827b6Dfcb4zWZUCePvKrozsUI83LvesJFClXDxVyyfww63e61g2fWAyfcb9BsD5nerzwbXeufECLf1V3IXbIvYqcB/gDEVvBCaLyA7gamCcXd4A2A5gjMkEjgI1nOW2HXZZsHI/InKziCSJSNL+/YW7oK1SquBd1j3nFA/FWbkE/zX6nPmUKpf1HyO37slh3DqgOW9d0TXix3N+8IH1IXc6wGSBnLiWn3J2CwVa5ufKXkU7hYiKjhEd6vHWlV053zGz2fVe6takWtDz/rdyFxV9xo2WxIkSOQZiInIesM8Y47va7N3ACGNMQ+Bj4GXXKQHuxuSi3L/QmPHGmO7GmO61ahWdjMFKKRWO8gECMZdOjaoG/JCJjRHuH9YmV8k5z+9Un1f/3tmrrM0jU71uT12zm6lr/Afbp2Vm8eOyHaRlZrmXSYpx1C/Q52HlsvER11GpH287K2B5j8TqiAhT7+rnPsbZ3V5ShNMi1ge4QERSsLoNzxGRSUAnY4xr0MG3gOuZ3AE0AhCROKxuy0POcltDrO7MYOVKqVIkWMqGkiRUIDaqgPKgXdilAXPv9e9GdLnli2Xc8sUyjqZm8K+vl7u7Ibs+OYN7vlvJZe8u4OUZ1jqBJ9M9XZ2+QeMvd/QtgNqrksa1ILlT18bVWOJYINw1O3jcJdbvNnUr07Wxp+WspOWryzEQM8Y8YIxpaIxJxBps/xvWGK4qIuJKmTsYz0D+icC19valwG/GGpgwERhtz6psCrQEFgNLgJYi0lREEuzHmJgvV6eUKha2PDuCD6/1XyexpHFmwAdP9949g1t5jb/Kb41rlHcvjRRMpyenM3HlLpo9OBnwpNCoXiGBX+z0FDNCZDg/o0HJnvGq8sebV3Rhy7Mj/MorObrlr+jZmJRxI71y5jmtDHPiyt5jp4vF4P5c5RGzx37dBPwgIiuxxojda+/+EKghIsnAPcBY+5y1wHfAOmAqMMYYk2Xf1+3ANKxg7jv7WKVUKRETIyVy7IevYFPvR3WuX+DX/99b/Lt/Ai0tA5A4dhLH7XUvZ23wjMd958puXsetf2oYAMPPCLxagFK+RCRgnjzXpJRQ+rW0lpiKi/U+f9+x07w0fYNXvrz0zGx6PjuTVg9PyfUklcISUfZEY8xsYLa9PQGYEOCY08Dfgpz/DPBMgPLJwORI6qKUUsVNRpb3B4IJMAi+INWqVIb9x9Pct1s/PDXE0f58JxuUjY8l+ZnhXmPHlMqNcL6IjB3ehnmb5pOa7v0Fov+LszmVkcXANrXdXZj3fOdZTqnpA5OD5ucrCjSzvlJKFZLnp3pmSKaMG8m/h7YGKLTlmXokVqe5vexRZlZkXTYbnx4esDwuNiZgC4dS+c3VtZ/p84XmlD0T2JV4+Nd1e93d6S6TVxfd1R8iW09EKaVUrtWrUpbdjiz1F3dtyMVdGxba44tYSXM37DnO0FfnRnRuQhhdR0rlxXf/7B1wNq5LnB3wZ2YH/hJx25fL6Nq4Ksv+8h9DdtuXy1jwwDleq0IUFfqXpZRSheS9q7vRuVFV1j4xNOeDC0BsjJBtDHM27svx2Mn/8mT5f/HSjiGOVCp/9GhanTMTgycudrWITVyxiw6PT+OnAKksAgVhLpv3Fc0FwzUQU0qpQtKxYVV+GtOHChEubp5fYkTINvDs5PVe5XPuHeDenvSvvtzSvzlVy3tyghVmq51SwbjGUs5cv4/jpzO561trHFjZ+OChzH/+1sm9Xa1C0cxzp12TSilVSojAjsOp7ttJDw9yj0/b+PRwYsQa89W+1yUd+wAAIABJREFUfhW2H/IcVxIXWlbFj+9sSYDTGVmczgjcVVmlXDyXdmtI9Qrx3PBJEtsPnWLk6/P55uZe9GpWo6CrGzYNxJRSqpRIOXASxwx/qpdPcG/7jgFz5Th75Lx2hVI3pXISH+Pf8tXx8elet5vWrMD3t/Tm0z9S6NHUCrbi7PNu+cJaIGj0+IXExQjJAfKZRYMGYkopVUqs2XnM63ao2Y4xMVKkp/yr0qd8Gf+VKdLt2b+3D2zhnoUMcM8Qz/buo6f8zsvMNhw+mU61Cgl++wqbjhFTSqlSIt2RsuK10Z1DHKlU0VMmzhOI/a2b97jFNvUqBT1vYJDl0w6eTCc1PZNUx9Jd0aAtYkopVQqN6twg2lVQKmKD2tYhNT2TtvUqe5VnhMiLVy4+8Bqvp9KzaPfoNMBaZi1a+fA0EFNKqVLi3Da1mbl+HzPuPjvaVVEqVz6w16T9ctE2r/I6lcoGPadS2XieuegMBrauTf2q5fhj8wGueH8RD/202n3ModT0Qkus7EsDMaWUKiU+vO5MTqRlUjFK6TOUyi8Jsd4jq3KaBXllzybubde6lqt2HHWXVUiI3t+EjhFTSqlSRIMwVRKkHPQkZ/1H36YRdSs6x5oBjL+6m986qoVJAzGllFJKFSvODPy1KkXWpdioenmv24Pb1cmXOuWWBmJKKaWUKlaqOnLgVY8wBUWVcvE8Oao9AP/s3wwJtcBlIdA2aqWUUkoVK+UdXYmXdW8U8fnX9E7kmt6J+Vij3NMWMaWUUkoVK8FSUhRHGogppZRSqlgpH8XB9flNAzGllFJKFSvlo5huIr+VnCtRSimlVKlQNj6Gvi1qMqB1rWhXJc80EFNKKaVUsSIifHFjz2hXI1+E3TUpIrEislxEfrFvi4g8IyIbReRPEfmXo/x1EUkWkVUi0tVxH9eKyCb751pHeTcRWW2f87pEey6pUkoppVQhiKRF7E7gT8C10uZ1QCOgjTEmW0Rcy5sPB1raPz2Bd4CeIlIdeAzoDhhgqYhMNMYcto+5GVgITAaGAVPycF1KKaWUUkVeWC1iItIQGAl84Ci+FXjSGJMNYIzZZ5ePAj4zloVAVRGpBwwFZhhjDtnB1wxgmL2vsjFmgTHGAJ8BF+bHxSmllFJKFWXhdk2+CtwHZDvKmgN/F5EkEZkiIi3t8gbAdsdxO+yyUOU7ApT7EZGb7cdL2r9/f5hVV0oppZQqmnIMxETkPGCfMWapz64ywGljTHfgfeAj1ykB7sbkoty/0JjxxpjuxpjutWoV/5kSSimllCrdwhkj1ge4QERGAGWByiLyBVbL1Q/2MROAj+3tHVhjx1waArvs8gE+5bPt8oYBjg9p6dKlB0RkWxj1LypqAgeiXYko0OsuXfS6Sxe97tJFrztvmgQqFGtYVnhEZADwb2PMeSIyDthojPnILn/RGHOmiIwEbgdGYA3Wf90Y08MerL8UcM2iXAZ0M8YcEpElwB3AIqzB+m8YYybn5iqLKhFJslsPSxW97tJFr7t00esuXfS6C0Ze8oiNA74UkbuBE8CNdvlkrCAsGUgFrgewA66ngCX2cU8aYw7Z27cCnwDlsGZL6oxJpZRSSpV4EQVixpjZWN2JGGOOYM2k9D3GAGOCnP8RnrFkzvIk4IxI6qKUUkopVdzpWpOFZ3y0KxAlet2li1536aLXXbrodReAiMaIKaWUUkqp/KMtYkoppZRSUaKBWC6JSCMRmWWvs7lWRO60yx8XkZ0issL+GeE45wF7Pc0NIjLUUT7MLksWkbHRuJ5IiEiKvTboChFJssuqi8gMex3RGSJSzS6PeO3RokhEWjte0xUickxE7iqJr7eIfCQi+0RkjaMs317forq2bJDrflFE1tvXNkFEqtrliSJyyvG6v+s4J+D1BXsOoy3Idefb+1pEmorIIvu6vxWRhMK7uuCCXPe3jmtOEZEVdnlJer2DfXaV6L/xENcd/b9xY4z+5OIHqAd0tbcrARuBdsDjWCk+fI9vB6zESoTbFNgMxNo/m4FmQIJ9TLtoX18O154C1PQpewEYa2+PBZ63t0dgzYIVoBewyC6vDmyxf1ezt6tF+9rCvP5YYA9WTpgS93oDZ2OlmVlTEK8vsBjobZ8zBRge7WsOcd1DgDh7+3nHdSc6j/O5n4DXF+w5jPZPkOvOt/c18B0w2t5+F7g12tcc7Lp99r8EPFoCX+9gn10l+m88xHVH/W9cW8RyyRiz2xizzN4+jrUgesClmWyjgG+MMWnGmK1Y6T162D/Jxpgtxph04Bv72OJmFPCpvf0pnvVCI1p7tLArnUvnApuNMaESChfb19sYMxc45FOcL6+vFOG1ZQNdtzFmujEm0765EO/k035yuL5gz2FUBXm9g4nofW23FJwDfG+fXyyu2673ZcDXoe6jmL7ewT67SvTfeLDrLgp/4xqI5QMRSQS6YCWkBbjdbub8yNE0GekanEWZAaaLyFIRudkuq2OM2Q3WGx6obZeXpOt2GY33P+iS/npD/r2+Ya8tWwTdgHeOw6YislxE5ohIP7ss1PUFew6Lqvx4X9cAjjg+6IrL690P2GuM2eQoK3Gvt89nV6n5Gw/wme0Slb9xDcTySEQqYi31dJcx5hjwDtaC6J2B3VjN25APa20WIX2MMV2B4cAYETk7xLEl6bqxx7dcAPzXLioNr3coBba2bFEiIg8BmcCXdtFuoLExpgtwD/CViFSmmF5fAPn1vi6uz8fleH/ZKnGvd4DPrqCHBigrtq95sOuO5t+4BmJ5ICLxWC/ol8aYHwGMMXuNMVnGmGysxdB72IeHWoMzUHmRZYzZZf/eh7XOaA9gr91k62q63WcfXmKu2zYcWGaM2Qul4/W25dfrm6u1ZaPJHoR8HnCl3RWB3TV30N5eijU+qhWhry/Yc1jk5OP7+gBWV1acT3mRZdf1YuBbV1lJe70DfXZRCv7Gg1x31P/GNRDLJXsMwYfAn8aYlx3l9RyHXQS4ZuRMBEaLSBkRaQq0xBrwtwRoKdbMogSsbq+JhXENuSEiFUSkkmsba6DjGqw6u2bNXAv8bG9PBK6xZ970Ao7aTbbTgCEiUs3u9hhilxV1Xt+US/rr7ZAvr6+977iI9LL/hq5x3FeRIyLDgPuBC4wxqY7yWiISa283w3p9t+RwfcGewyInv97X9ofaLOBS+/wifd22QcB6Y4y7+6kkvd7BPrso4X/jIT6zo/83borALI7i+AP0xWqOXAWssH9GAJ8Dq+3yiUA9xzkPYUXVG3DMIrHP22jveyja15bDdTfDmhG1Eljrqi/WWJCZwCb7d3W7XIC37GtbDXR33NcNWIN9k4Hro31tYVx7eeAgUMVRVuJeb6xAczeQgfXt7x/5+foC3bE+2DcDb2Inlo72T5DrTsYaB+P6G3/XPvYS+/2/ElgGnJ/T9QV7DqP9E+S68+19bf/PWGw/l/8FykT7moNdt13+CXCLz7El6fUO9tlVov/GQ1x31P/GNbO+UkoppVSUaNekUkoppVSUaCCmlFJKKRUlGogppZRSSkWJBmJKKaWUUlGigZhSSimlVJRoIKaUUkopFSUaiCmllFJKRYkGYkoppZRSUaKBmFJKKaVUlGggppRSSikVJRqIKaWUUkpFiQZiSimllFJRooGYUkoppVSUaCCmlFJKKRUlcdGuQG7VrFnTJCYmRrsaSimllFI5Wrp06QFjTC3f8mIbiCUmJpKUlBTtaiillFJK5UhEtgUqD6trUkRSRGS1iKwQkSRH+R0iskFE1orIC47yB0Qk2d431FE+zC5LFpGxjvKmIrJIRDaJyLcikpC7y1RKKaWUKj4iGSM20BjT2RjTHUBEBgKjgI7GmPbA/7d31+FRXVsDh387TnAIViwEd0txtyJtqettqdL2o3arUFoqVKjLrQttaUu9FO7F3Z3iUAghSJEQgof4/v44ZyZnNJNkkoms93ny5Mw+kn0yM5mVLWu/ZZa3Am4CWgNDgY+VUsFKqWDgI2AY0Aq42TwW4HXgXa11U+AUcHfBb00IIYQQongryGD9B4BJWus0AK11olk+EvhJa52mtd4PxAFdzK84rXW81jod+AkYqZRSwADgN/P8b4GrClAvIYQQQogSwddATAPzlFIblVKjzbJmQG+zS3GpUupSs7wucMhy7mGzzFN5deC01jrTqbzY2nzoNPuTLgS6GkIIIYQo4XwdrN9Ta31EKVUTmK+U2m2eWxXoBlwK/KKUigGUm/M17oM+7eV4F2YQOBqgQYMGPlbdv7KzNVd9tBKAhEkjAlIHIYQQQpQOPrWIaa2PmN8TgWkY3YyHgT+0YR2QDUSZ5fUtp9cDjngpTwKqKKVCnMrd1eNzrXWs1jq2Rg2XGaBF4tjZ1ID8XCGEEEKUPrkGYkqp8kqpirZtYAiwHfgTY2wXSqlmQBhGUDUDuEkpFa6UagQ0BdYB64Gm5gzJMIwB/TO01hpYDFxn/shRwHT/3aJ/hQTnNOBNXXuQVfuSAlgbUVZdSMskeuxMpq49GOiqCCGEKABfuiZrAdOMMfWEAFO11nPMYGqyUmo7kA6MMoOqHUqpX4CdQCYwRmudBaCUehCYCwQDk7XWO8yf8TTwk1LqZeAv4Cu/3aGfhQTlxK7PTNsGwBvXtWPzodO8enXbQFVLlDH/98MmwHgNXh9bj6xsTURocIBrJYQQIq+UETuVPLGxsToQCV1PXUin48T5bvfJmDFRVKLHzrRvd25YlY0HTvHLfd3p0qhaAGslhBDCE6XURlsKMCtZa9KPUjOyAl0FUQZtPHAKyGmhFUIIUXJIIJZH3toPz17MKLJ6iLItqoLr4hNxiecDUBMhhBAFIYFYHnnryv15/SFem7WL9MzsIqyRKGuysjVJ59Pd7pNWWSGEKFkkEMsjWxj2+OBmLvvenr+Hz5bF890at+t6CuEXs7cf9bjvkyX7SM3I8voPgxBCiOJDArE8sn2+VYkMtZeFBDnmpA0LdpejVgj/mL39mEtZzYrhALy/cC8tnpvD4HeXFXW1hBBC5IMEYvmlFH2aGUll/355mMOucmG+LlggRN7N3OraIta8dkWHx7bxYrdPXkfnifOJPyHjx4QQojiSiCGPtGW4/pe3x3IxI4vgIEWTmhXsH35pmTJORxStu3o2Yvlex+TCbV+Yy7lUYwnXvYnnialRIRBVE0II4YW0iOWVGYcpICwkiMrljC7KBY/15atRRnqQ1AwZrC8KX2zDqvbtrGzN+zd1cNhvC8LAWCNVCCFE8SOBWB7ZPs6Um2FgPZtEATJzTRSepPNpAPRrXoMJV7Syl59Ly2Bkh7oez3tn/p5Cr5sQQoi8k0Asj7S9Rcw1EgsPMX6daZK+QhSSy8xB+EFK0a5eFR4e2BSAmCij27Faedf8YmB0Tco4MSGEKH4kEMsndy1iSinCQ4JIkxYxUUhOXjDyhx1KTgHg34OasuLp/rSvXwWAlU8PYNNzg3mwfxOXc++ZsoHzaZlkZMk/CkIIUVxIIJZHa+JPet2flpnNZ8vii6g2oqx6/6aOgBH816saaS8vFxZMtfJhbD9yxuWc+BMXaPP8XJqOn11k9RRCCOGdBGJ5cODkBR79eTMAVSPddwHZjPtjq4wVE4WmfHiw1/3jhrUsopoIIYQoCAnE8mBlnNEa9srVbbisdS23x3Q2Z7L9uO4QGxJOFUo9srO1zIIr40KDvb91rXnFtjw/pLCrI4QQIp8kEPNRemY2R05fBODydpeg3A0SA+7p1ci+/dRvW7xe83RKOtFjZ/L4L96Pc9Zk/CxinpnF+bTM3A8WpdIlVcrleszGZwexecJgKpcLZY8l6XBYLkGcEEKIoiN/kX30wPcb+XBxHGHBQVQI95wHt4qly/LImVSv3ZPzdh4H4PdNh/NUF1tj2Iq9J/J0nihbqlcIt78ew0Jy3uodzIH9QgghAk8CMR+tjj9JaLBi6r1dCQ7yvJZk54ZVGT88Z3xOp4nzPR771G9b7dv5WaR555GzeT5HlFxnUzMKdL4ttYV1dQghhBCBJYGYD1IzskhJz+K6zvWIja7m9diwkCDu7RNjfxwZFozWmgMnL7Buf7LH88752M1oHRuW2zghUbq0e2EeAGP6N87X+ZueG0yPxtX9WSUhhBAFJJ/kPthnJsJsUK28z+f8eG83AJLOp/Pc9O30fXMJN3y2mvcWuM9wPnrKBp+uO2fHMft2uTBj5tyh5BQW7jruc91EyfP2vL/t2xUjQgt0rXw0vgohhCgkPgViSqkEpdQ2pdRmpdQGp31PKKW0UirKfKyUUh8opeKUUluVUp0sx45SSu01v0ZZyjub148zz/Xc9xcAHy6KA3JmRPqiu6Xl4fs1B+3b7y3Ya9+OCM359a+JTyYh6YJDi9eKvUmM+WGTw3WtH6Ivz9zFx0viuPLDFdz9rW+BnCiZ/mO+BgG2Hj6d7+sUr3eWEEKIvLSI9ddad9Bax9oKlFL1gcHAQctxw4Cm5tdo4BPz2GrA80BXoAvwvFLKFtl8Yh5rO29ovu6mkGSZwVFeArHc/GfhXlIzsmlXr7K9rN9bS7jpizX2x7dPXsvMbUdZFZdkL3P+IJ259SinUoyxQ+cKOIZIlAxJ59ILdL40iAkhRPFR0K7Jd4GncPzbPhKYog1rgCpKqTrAZcB8rXWy1voUMB8Yau6rpLVerY0R61OAqwpYL79Jy8xi3s7jNKgW6XWQfl7c/91G3jYXYe7iNOZs3f5k0jKNmZa2xrFbvlyL1poVe5P4baPjDEvrmJ/XZu/2S/1E8fav7g3zfa67NVKFEEIEjq+BmAbmKaU2KqVGAyilrgT+0Vo7J8GqCxyyPD5slnkrP+ym3IVSarRSaoNSasOJE0WTumHhrkQADppr++WFc5qAvs1qAMY4rzZ1KwEwum8Mn9/W2eE4d4uG/7z+EP/6ai2Ldhv1+e3+7gB8sXw/LczknS3rVMpzHUXxZ02B8s4N7bm8bZ18X2tFXBIbDxROomEhhBB552sg1lNr3Qmj23GMUqoPMB6Y4OZYd/9y63yUuxZq/bnWOlZrHVujRg3fal5AJ8+n5fvcX+7rzq1dG9gfhwbn3Or2f85SrXwYNStGkJHleLtT1x7E2dg/tjk8ts7erFkpAoAQP7XYFbWDJ1PsyXKFq2NnUu3b13SqR5Afnuf8pEsRQgjhfz4FYlrrI+b3RGAa0BdoBGxRSiUA9YBNSqnaGC1a9S2n1wOO5FJez015sZB0Pv/jccJCgnh8SHP74yvaX+Kwv0qkMfvt2NlUh/IPFu4lL2wfqhfTS+baln3eXEyPSYsCXY1ib9ywFn67VnzSBb9dSwghRP7lGogppcorpSratoEhwHqtdU2tdbTWOhojmOqktT4GzABuN2dPdgPOaK2PAnOBIUqpquYg/SHAXHPfOaVUN3O25O3A9EK413yJjooE4NFBTfN1vi2JZtdG1egeU53hbWvb9z13eSsA+jU3Wvc6NTC6Mt11TXqzfK8xmP+l/+3MVx1F8ZZpDhb0ZVmj3Nxn5ri7IMtjCSFEseBLi1gtYIVSaguwDpiptZ7j5fhZQDwQB3wB/B+A1joZmAisN79eMssAHgC+NM/ZB8zO+60Ujumbjca5tnUr53KkZ/GvDuen0d2oWSmCj2/NGQ9WuZzRIta4RgUSJo2gW4wx8D4rW3vtOpr7aB8A7ugR7bIvSxYDL3Uys43A3B9dz/2a1wSQdUqFEKKYyDUQ01rHa63bm1+ttdavuDkmWmudZG5rrfUYrXVjrXVbrfUGy3GTtdZNzK+vLeUbtNZtzHMe1MVoAEutisb4q7pV898aERSk3C4SXtFpzcqbu+SMJ9t8yH2uqFHdG9LcHJzvLp3Gs39ucykrKX7feJhf1h/K/cAyIC0zyx4sZZpjCP0xa7d8uJEE2DruTAghROBIZv1ctLrEmIlY0wzI/OHz2zrTtVE1GlZ3zNRfv1okMVHlaRRVnjfnGpnUL42uyvQxPfnfQ724o0c0E65obT/+8nZ1eP3atky5q4u9bMuhM36rZ1F7/NctPPV7zvqbP68/SPTYmZy5mIHWmg0JnpeIKm1u+nwNbZ6fC+S0coYEFzwQO5dqBHfP/rm9wNcSQghRcCG5H1K2ZWSZ3UJ++BC0GdK6NkNa13a7r3PDqizZc4JV+04CcHevRrQ302C0ceoeVUpx46VGK9rt3RsyZfUBe/dmafD070br3uxtR+2zRj+5tRPDCpC+oaT466DRIrpg53ESzxkzdyuEF2xpI4BWZoqTkR3cZogRQghRxKRFzIv5O4/z8sxdAIQV0QLbu4+d48S5nJQZvZv6lqbjhStaExqsWLUvqdR171mX93lj7t9kZGVz59frHFYcCLSMrGzu+mY9Wzx0KefXPVM28Mw0IwitWTG8wNeLCDW6JhtUiyzwtYQQQhScBGIeHDuTyr3mQtzD2tQmPKRoflXb/nHsWiwf7lujZVCQokJ4CLuPnbN37xWjoXYFEhudMxbudEo6TcfPZvHfJ7jly7UOa3MGUlzieRbtTmTkRysLbUZizUoFD8RsLbsri1EQK4QQZZkEYh7YxtAMaVWLT/7V2e1g+8IwwUxpkR/WGZOvztrFoHeW+qNKAWcb1wTY19W0iXlmFhOmbyczK28pP/zNmnLk8V+cF5vIO1vaE6vIsIKPJLDNvFwhgZgQQhQLEoh5cG/vRnx4S0fevqF9kf7cu3o14oObO+br3LOWgOXzZfHsO1EyknbG1HCctDB6ygbm7zxuf2xb1smTKasPcOc36wulbr6yrpqw3odJBRfSMpm17ajH/YWVnNf6D0VKeia7jp4tlJ8jhBDCNzJY34OuARz0XjHCv0+L1ppG42ZRMSKEbS9c5tdr+4WGEe3qUDE8hJ/WH2LezuPMswRivrAltQ0Ua2vkyQvpaK29tqI++vNm5u88zqyHe9tn5lrVqBhuX9903LAW9pQl/tRqgjErc8vzQ+w57YQQQhQtaRErhtLzmFnfm+xsbc/Mbu3iKyzJF9LZdDBvi0pna02wUvy5+R+vx1kHq7cqpAXOE8+l8tWK/Xkee5bpdPzb8/Z4PHZ9QrK9xe9CuvvnxLpg/H19G9sTsRaG9i/OY8zUTfbHq/edNNKGOHUDa61ZvvdEsRmXJ4QQpYEEYsVQXpc4skmYNIKESSNoVquCvSxLa6xj9k9dyP/amb54bvp2rvl4FSkeAgx3NBCkIDXD+32vGz+IazoVXtqFjKxsXpu1m4n/28nWf/KWjy3TaeH2xX/ndKfuPX7OIZP99Z+utm/v97DmY1YRT7SYufWovVXv5i/WAHDj56sdjhn7+zZu+2od36xKKNK6CSFEaSaBWDGUlV2wFrFf7utu3z6dkuHQbfaGmSi2MESPncnMrca4pyOnL/p8XraHbrwFj/Wxb9sWSH/92nasHDuAxjWNYPP9mzpQt0o5hxak/Gr27Gym/WW0yv19zLexUxfTs1i0+7h9XNhDA5oAOS1aCUkXGPzuMq78zwrAdWmhN+a4fz7Wxp+kYfVI4l4ZlvcbyaeBby8B4NauRm66Sk7dlT9vMNKibMxji6cQQgjPZIxYMVTQCYBVInNm3CWcvECSJS/Zj+sO8to1bQv2A3ywfG8STWr6Nq5Ja1DAmnED2XHkDHd/a6QNseW8Alj8eD8AQoODqFulHC+PbMOQVrW4ov0l/L7pH85czHBzZcP8ncf5cd1Bbry0Ppc5JdJduucEd3+znpga5R1aDtOzfGuRGjV5Hessg/P7NqvB58viqRAeQvKFdPq9tQSA+KQL/PvnzfZAzybpfBrOYl+eT9L5dJLOpxNSRPnrABJOphA9dqb98br9yW7Huu06epYzKRlUjpRxZUIIUVDSIlYMXd6uDpe3q8Pyp/oX+FoTpu9wmHU4vK37jP4FtXTPCYfHL/53p31VgtwcPnWRA8kp1K4cwcCWtezldavkrO9Z1SmdQ+XIUK5ofwlgBHHWKOr56dt57s/tRI+dyeZDp7l3ygYW7U7kvu82smqf46D+UZPXkZmt2XP8vEP5Nyv351rvW79c4xCEgTG+Ly0zm8OnLtJp4nyHfdYgrHYl1yWzDiWnsGzPCZLOF273sc2n/+qU6zHWdCHXdDS6heNPXKD9S/OISzzHt9JNKYQQBSKBWDEUERrMh7d0on4Bsp/bWr12HT3LrxsPA8Zgd2vWfn8aNXmdS9mmA7l3YaVmGGkaNlqOtXVD+pq7TSnYefQs83YcIzUji29XH+C7NQcAuOqjlQ7H3vLFWq+TIdaPHwTAvhMX+HHdQY/HdZo4n5VxJ13KY2oYXaYzvaSmADh2NpW7ejaiQngIWmvm7ThG7zcWc7vl97h5wmCv18ivnS9dxoZnBzms2tC7aZTbY5/4dQvn0zJ5e97fHD7l2N1842dreH7GjkJLYCuEEGWBBGKlVJCbGCYlPcuhu6+w3fj5Gk6neG/dSXMzQH/pk/1Z+8xAn3+OAjKyNKO/28iXy+NzPT7xXCpgjNdqWN0Idre+MISZD/ciqkJOy9u4P7a5zBD875YjRI+dSbJl0sMD/RrbJ0rUruza0jV+eEu39dj2z2nOp2Xy0eI4Rn+30WFf95jqDl3M/hQZFkJUhXCHVRueGNLc7bGLdifS5vm5/GdRHOsSkh1WmDhp/g7eme95hqgQQgjvJBArpZyXSgJoWaeiy+y+wjY/l3xgFzNcE5dWLhdKLTddd754y0vaCBvb5IU2z8/lwEkjV1eliFBaX1IZpRT7Xh1uP9aWz0xrzUeL43jox79crvf00BYOj61dqnMf7cOt3YzB73f1bGQvf2JIM/sYOnd1Xh3v2tpWGO7rEwNAu3qVmfNobyZe1Ya6Vcqx7Mn+xDas6nJ8WmY2Y/o3JtgS6ZezBPeHklOkhUwIIfJAArFSqmG18i5lYSFBbgMff2htJiW90hy3ZfPWPNdZgbuOnuX42VQupmfZ6+NtAkG5XFrxFv99wut+gJdGtrbPZMzp+OlrAAAgAElEQVTIJRgNDlLc1q0hAPd/v5FDySlsOniaN32ccbr8qf6sGjuAhEkjaF67IpFhIex7dTgTrmhFwqQRxL0yjAcHNGV/0nmP13hpZGufflZBjRvekoRJI1BK0aJ2JW7r1pCVYwfQoHokA1q6z10WHhLsMBP3w8VxRI+dSWZWNr3fWEzr5+cWSd2FEKI0kECslLqpS30AhpqzBLs0qsbKuJNsPnTa74uBa63ZceQsdSpHuCzPdG2neg6PT6ekM+z95XR9dSEtJ8yxj1mr6mEG3vd3d2XB433zXKfPb+vs8Hhom9qMNlt/Fuw6zhVmOglPHhnU1L7d+43FXPvJKp9/dlCQ4hJLqxjg0IJkmwl5eTvHoNUmYdIIbu8e7fPPKyxLducEuHf0iAagS3Q1h+5Jq+WyfqUQQuSZBGKlVMWIUBImjaCXOQi7crlQOjUwWoTymzDWk5dn7gLg6Blj7NXb17fnmeFGd10dpzFTzrMTb/jMSBoa7qHVq1fTKIeuPm8eNnN4AQxpXZvdE4ey/Kn+JEwaQc2KEfZgaNLs3W67bq2iKoR73Hd1x7p8fcelPtXJm5u7NHApq+5mse9AGdI6ZwbrC1e2Jv7V4fxyf3ePgZi13N/BvhBClFYSiJVykWFGgBMRGswIswUmNY/dk+fTMhk1eR27jp5l/LRtHDMDLjCWNPpqhWOqh2s717MHGVPXHXLYd8rD4P3IAkwi2PvKMHZPHMpjQ5qz/Kn+bHrOmG0YERrsMPN0sYfFwyd66AZsW7eyS9nzV7Ti9Wvb0a+5MePwZrPlMT+srWR9mhnXc7fuZKDc0zuGQS1rcmOscY9BZn2PWp7/F6/M+d3d8sVa+3ZhdYELIURp41NCV6VUAnAOyAIytdaxSqk3gSuAdGAfcKfW+rR5/DjgbvP4h7XWc83yocD7QDDwpdZ6klneCPgJqAZsAm7TWhdNMqVSLsxspYgICeJXMzP6poOnGNCilrfTHMzdfoyle07Yc4VN33yE+Y/1oU7lchw9k5PS4MH+OS1SttmZu446Zqi/mO7+A7og62CGBgdhi+O8pfwY078JP63PCQyv7VSPt29o7/F451azD27u6DAGLmHSiHzW2NWLV7bmxLk0WtTx/+LeBfHlKNeWP2vG/VE9osnIyra3itocP5tGoyjJFy2EELnJS4tYf611B611rPl4PtBGa90O2AOMA1BKtQJuAloDQ4GPlVLBSqlg4CNgGNAKuNk8FuB14F2tdVPgFEYQJ/xgaOva3N+3Mc+OaGXPKu9pWR1PnBOznk/L5JGfNgMQZMn1dW/vGPt2iKW152J6FvdO2cCP6w4Sb66tuGrsAIdrRkflP2ear6xB2vKn+nsNwpwtf6q/y0QEf7AHyqFBdGlUjUoRxT9bfffG1R0e392rkcsxa4po1qcQQpR0+e6a1FrP01rbmjHWALZR2SOBn7TWaVrr/UAc0MX8itNax5utXT8BI5WRtXMA8Jt5/rfAVfmtl3AUEhzE2GEtqBwZyjAzq/7uY+fydI0EM8WD1br9yVxMz+JQcs6+ihE5LSDWZKwtJ8xh/s7jjPtjm/34qpFh3NEjmi7R1Vj+VH+fl0PylzAP45zcSZg0okDJdb2xTaaIDC05rUcNzN/FmP6NAfeJd5+Ztq1I6ySEECWVr3/9NTBPKaWBz7TWnzvtvwv42dyuixGY2Rw2ywAOOZV3BaoDpy1BnfV4B0qp0cBogAYNXAc6C+/y82F/LjWDT5fuc7uv5YQ5Do+D3GWRdWJb5icoyBgAHighPtR16j1dWbs/OdfjCuKN69rxQL/GJWrdxqgK4Wx8dhBV3SSc7RJdjXUJychYfSGE8I2vzQI9tdadMLoVxyil+th2KKXGA5nAD7YiN+frfJS7Fmr9udY6VmsdW6NGDXeHCC8iwnKe7mV7cs+9Bb4Pur7HTfeUNyFBgZknYht4bs0q70mPJlH8e3CzQq1PRGgwLesUnwH6vqpeIdwh8B4/vCVT7+3Kz/d1s5dJYlchhMidT5+GWusj5vdEYBpGNyNKqVHA5cCtOme++mHAOpWsHnDES3kSUEUpFeJULvwsqnxOSoZ7p2zw6ZzdR33rxhw7rIVLWfNa7rsbL6kc4TBjsCi9ek1bNk8YXKRLPZUF9/aJoUfjKIduSknsKoQQucs1EFNKlVdKVbRtA0OA7eYMyKeBK7XW1kFEM4CblFLh5mzIpsA6YD3QVCnVSCkVhjGgf4YZwC0GrjPPHwVM98/tCStrC0ZaZjYnz3tfAHzP8XPM8rB49cAWNRnSKmfmpS1JqdV3d3exbz9maVm61cxaHwjBQarQ1nAUQggh8sqXQUO1gGnmf7ohwFSt9RylVBwQDsw3963RWt+vtd6hlPoF2InRZTlGa50FoJR6EJiLkb5istZ6h/kzngZ+Ukq9DPwFfOW3OxQefbYsnmc8LEi9Ki6JW75cS0WzC2/js4OoEhlGcJBCa41Sip1HztrXYnTH2v338MCm9sWhnZO8CiGEEGVVroGY1joecJnnr7Vu4uZw275XgFfclM8CZnn4GV2cy0Xh+txLILbvhJEB/5w5zqda+TB7t5Pte6Vy3l8+tu7HZrUqAFCzYjiJ59Lo0Tiq4JUXJYItaBdCCOFeyZkzLwpF4tlUalZybaF6bvoOh8fuPkzrVY1k6r1daV3HNQM9GAPRv72rC+3MDPVrxg3kXGpmiZohKPIuYdIIosfOBCA1I5tyYTIeTwghPJEljsqYt693bNzMyNZkZGVz4OSFfF2vR+Mor4FV32Y1qGqunxgUpCQIKyPGmZM3MrL9u66pEEKUNhKIlTHXdq7HmnED7Y+11vxn4V76vrmEf05ftJdZWRO1CuEL2wLgWVmSUEwIIbyRQKwMql05gmdHGGPDtIZPl8YDcPyssZizc+6wYW1qF20FRYkXbM6ilRYxIYTwTgKxMqqa2V2YrTXp5lqS13y8itMp6fy4zlgAoVYlI+/Y5e38v8aiKN1CzYkamdIiJoQQXkmfUxllW6w72+lzssNL8+3b1cqHs/aZQUVZLVFK2GbMZjm/wIQQQjiQFrEyyjYJ8slft3g85uNbOxVRbURpE2rrmsySrkkhhPBGArEyypaOYsOBUwC0vsR1vcNGUeWLtE6i9JAWMSGE8I0EYmWU81KPV3Wo63FtSCHyKjTYeIFlyBgxIYTwSgKxMio907HLKCRYMefR3gGqjShtQoLM9BXSIiaEEF5JIFZGnU7JcHgcEhzkkD1/yRP9irhGojQJtrWISfoKIYTwSgKxMuromYsOj8PMD86fR3fjmzsvJVrGh4kCCDMH60v6CpEfv288TPTYmaxPSA50VYQodBKIlVHOk9kyzS6krjHV6de8ZgBqJEqTEHMQ4g2freaOr9c57NNakxng2ZQv/ncHvd9YFNA6CM/eXbAHgOs/XR3gmghR+CQQK6MynbqM2terEqCaiNIoJDjnT8uSv0847Bv0zlKajJ9NWmaW82lFYn/SBb5emcCh5Iu5HywC4rrO9ezbq/edtG9rrek0cT6fLt0XiGoJUSgkECujxvRvYt/+4OaOtKlbOYC1EaVNWLDjnxbr+qX7ThgLzL8ycxcp6ZmFVofEs6mMn7aNzKxszlzMYOzvWzmTksHtk9faj3GetCKKh6gK4fbtm79YY98+m5pJ8oV0Js3ezT3frue12bsCUb0S71xqBuP+2Mr5tMJ7/wnfSSBWRtWqFMHqcQO4sv0lDGlVK9DVEaVMSLBjfhRbGgtrQDZl9QFaTZhbaHXo8upCflh7kA8Xx/H9mgP8tP4Q7V+a59AS1vP1nO7JY2dSufPrdS7jJ0XR85QIeNqmw/btBbsS+WxpPOdSM9weKzybsvoAP647xAcL9wa6KgIJxMq0OpXL8cHNHYkIDQ50VUQpE+KUqM7WFT5985Eir8t7C/ayMi7J7b4T59Ls291eW8jiv0/w1G9bi6pqwgNPkzxe+O9OlzJr16Un0zf/Q/TYmSSdN57vjKxsbvtqLRvMyQAX0jLLVEBne91/viyei+mBGSIgckggJoTwu8rlQh0e/77pHwBmbHENxDaaqzsUplW5fFhbxxwt3+s+aMtNVrYmW/Km+cW0v4zXy81d6ru8lpwt23vC636Ajxcbz69tvOL/th5h+d4krjMnA8S+vIC2L8zLcz3TMrM4diY1z+cFWueGVe3b907ZEMCaCJBATAhRCGpWinB4/Nyf28nIyqZ7THWXY6//dFVRVcutH9YeYNLs3Q5lv6w/lKdrpKRn0viZWfzfD5v8WbUya+fRswBUiQzjzMUMUjOyHLq1rb5fczDX6/19/BwAT5hr6ypyWmzPpmZwMcNoFTpz0fdWsS2HTtP82Tl0e20hF0rYWKsK4SH27RUeWotF0fEpEFNKJSiltimlNiulNphl1ZRS85VSe83vVc1ypZT6QCkVp5TaqpTqZLnOKPP4vUqpUZbyzub148xzlWsthBAl2fsL9trHji19sp+9vLAakUKDPf8ZSZg0wr49ftp2l/1P/Z637snYlxcAMGfHMXtZVrZmx5EzebpOaRaXeJ7osTPz1IL0yRKjJavFc3NoNG5WrsfvT7pAaoZjV1viWceft3zvCR79ebP9cTtLS9jfx84RPXam/etMiufAzNZqByVvcXvnMZwlLZAsbfLSItZfa91Bax1rPh4LLNRaNwUWmo8BhgFNza/RwCdgBG7A80BXoAvwvC14M48ZbTlvaL7vSAhRLH24OM6+5FGVyDCev6IVADGFlDy4Wa2K9G9ew6Fs84TBbH/xMgDmPtrH5ZynhjYH4M6e0Xn6WSmWcTbzzGDshRk7GPHBCrYePp2na5VWV3+0EjDG4iWeS/U4KeKub9bneq2Fj/d1KcvIyqb/W0sY/d1Ge9mTv26hy6sLHY677at1zqfaPfenY1B+nZfW2umbcwKxwpx9m56ZzYeL9nI2NcNvAZNz4+IPaw/45boifwrSNTkS+Nbc/ha4ylI+RRvWAFWUUnWAy4D5WutkrfUpYD4w1NxXSWu9Whttz1Ms1xJClFCf3daZRk5B1vvmLK3gIMXt3aMBiE+6wNI9uY/zyausbE1YSBAJk0awbvxAEiaNoEpkmL1bpmp517FH4SHGxJVaTl2reTH6u42cTknnuzXGh9uVH67M97VKk4ZRkfbtLq8spPtrixxakrTWfLQ4jkW7E+1ll1R2/zzERJWnZZ1K9sdnUjKYs90IgJftOUH8ifMA/LoxZ5blgBa5J6q2dWHa7E087/FYa+LrzYcKL9hu9uxs3pq3h3YvzKP18/6dZTyywyUA7D52LpcjRWHyNRDTwDyl1Eal1GizrJbW+iiA+d32qqwLWAdYHDbLvJUfdlPuQik1Wim1QSm14cQJ///hFkL4z2Wta7u0Op1LNf6jD1JGMGYzarLnVor8yszW9sXHa1Z0/UC37bOKrm4EC86Z/8+lZngdP9QtpprD4w4vzXd47Gl8U1lyXad6LmVNx8+2b286eIo35/7tsP/hgU1dzrmjRzRKKWY/0ttedvpiOlUjw+yPh72/3OW8z27r7PB4dJ8Y2tf3nsg6ItTzR6S1a9LaCucviWdTiR470+/XBeMDHeD27g0JDVYF+sdDFJyvgVhPrXUnjG7HMUop1zb9HO4GZuh8lLsWav251jpWax1bo0YNd4cIIYqRsBD3f2KCzGGgtQvxAyArWzsEe87KWdK27H9tOHMf7UN/s5Uj02ngWo9Ji2j/ouusuphxMxk1eR3nUjPp26wG17oJNsAYu1TWXcxw33138GQKAFsPO46na1mnEjd1aeBQ9vDAprxwZWv749u6NQSg75tLWPJ3TktaWmY2y/eeIKaG0SI7vG1tQoODuL9vY/sxzwxvSbtcElmnZmQT56VVzOqXDYc4dSGdLX5qHfPUSuwc1GdkZRcg0FdkZGn7WDwRGD4FYlrrI+b3RGAaxhiv42a3IuZ327vgMFDfcno94Egu5fXclAshSgF33Uu2QGxkR6NrpGbFcJdjCiorW7vkM7MqF5YTiCmlaF67IkFBiiCFfSybja0lDyA7WxM9dibPTNtGtjY+MHccOcv5tEx6NXWdFQqQXsIGcxeGixnu81V9v/YAfx08xTZLIFY+LNihxctmoFP34pDWOcmov1yx32HfbV+tI95cxeHjW43WsH91cwzsfDHywxU+HTdvx3Gu/nglIz/yT1e0p38i0izj0TKysmk6frZLS2Ju3AVu1px6omjlGogppcorpSratoEhwHZgBmCb+TgKmG5uzwBuN2dPdgPOmF2Xc4EhSqmq5iD9IcBcc985pVQ3c7bk7ZZrCSFKuFXjBvLc5a0cymwzGp8YYgyO97TE1oq9Sazal7/p9adS0gnyEoh5kq3hYnoWqRlZLuthbjyQzEeL4wCYuvag075TLq06NkPfW16oyzmVBKkZWZQLDSZh0gh+Gt2NazoaI1A+XxbP1R+v4g+zq69H4+qsf3aQ22uEO3UV5ta1CI7JhetULgfAfX1jAMi2BCTf3d3F7fkXfEx4umDXcRLM1r38Dt7/euV+osfOZOGu4zz2yxa3x9gmhvx97Bw/mWlWPs6lRSslPdOhTglmC63WOa3Gl76yIF91FgUXkvsh1AKmmRklQoCpWus5Sqn1wC9KqbuBg8D15vGzgOFAHJAC3AmgtU5WSk0EbFNiXtJaJ5vbDwDfAOWA2eaXEKKUcI6HbBlqQoODaFevssMHotW/vjLWhbSmm/DFP6cvci41k982Huat69vnub5frtjPlyv2Uy40mF0TcyZx3/rlWlI9dLF1aVTNpVWhd9Moe4LY1ftOMrBl2V1O7GJ6lr0VsltMdVrUrmgPvqyu6liXyDD3H00taldyeOytxdPGFnSB0cpkfS2dSkm3b5c3J3G0vqQSMx/u7fP4rDXjBtLtNceZmYnnUqlXNdLDGZ69aK4ccPe3OUlWw4KD6NSwCmvijY9LW8viZe8t8/m6bV+YZ0xeCQ6iT7MaLNh1HICTF9K5rVtDvlmVABgJam0TVkTRybVFTGsdr7Vub3611lq/Ypaf1FoP1Fo3Nb8nm+Vaaz1Ga91Ya91Wa73Bcq3JWusm5tfXlvINWus25jkPahnZKkSpEuQlNaBSymU6PTh2n2Rna+ISz5F8Id31QDd6TlqU+0HAz6O78cXtsR73X8zIcvhA9hSEgdF9Odhct3XqPV1Z9mR/xvRvYt8fElx282f/dfAU36054PD8VbEMrrca2qa2w+ObLq3v9jiAyLAQXryyNcMs53xwc0eHY6qV99ztfdSS06xd3crc0rUBH91ipL709rqwaVAtktqVI6ga6TgDt9fri4keO5P0zIKM3zJseG4Q13XO+R18siTObZDo7efYutrTs7LtQRhAh/pV7DMnAab/JaOCAqHs/mUQQhQZbw0XCty2iFkTeD7x2xYGvbOMThPnuxxXEF1jqtuDp7z69f7ujOre0P548h2xXNn+Era+MIQeTaJoUD2SbjHVeeXqNoD7eywrrv7Y99UTKoY7toZd3dHtJHq7UT2i+eRfOTMir2yfE1hEV4/kLi854f46aAys//qOSwkJDuLVq9sSbaZcGdyqltcgMCw4iOFt6xjXmTDE7THNnp3N/d9vZG187uthOs/UBbi1awMqRYRyXed6vHldO8DzSgKnPSSfvcrLmLWaFcPp2KCqfVJDfocBiIKRQEwIUfi8tIhZg7Tv1xzg1Vm7XI75Y5NrF5YvFjzmmvjTXy6Nrsajg5pRv1o5Fj/RjzqVy6GUolKEY+tIu7rGOCZPC1mLHN1jqtu7rW0qRBiBWW55wBY81pdFZqLX6uXDePKy5ix5sr/L9axsee46R1d1u79a+TC3g+a11mRkZxNmyVD/1ahY3ruxg8uxc3cc58bP17Asl1x57iZ0PDQgJ32HpzU3bSlX+ryx2O1+bznObL+bGQ/2AuDPzUeYufWo13qCkWpkfUKy/fGqfUl8vCQu1/OEe76MERNCiAKxfpatfWagwz6llL216Fkzs/m9vWPIzdcr99OsVkV6NokCIP7EeWZsOcKXy3NmzzWpWaGgVXdr5sPGB1fV8mEsf2qA12Nty8lkZZeNmZM3fraaIa1rc3evRgD25KoA8a8O93jexJGtGWa2MFm1vqQyU+/p6jFYsrE+1xufG+xTXRc93teYXeuh2zgkOIisbI3W2h60pGdm89HiOLQ2xjjaDGxZi73HPSdGnbHlCH2aOaZdOp+WaU8w/M8pY6WB9vWr8Pv93Tl6JpXalhnH7rr3lz7Zj7X7k3nqt62cS8uk0biZ/Ofmjlze7hKXYxvXKE+fZjWYte0ox886jmWMtKRyGTN1E/EnmvGQmxxuYOTUu8Zs4UyYNIKDJ1O45QtjLOdVHepySZVyHn8Hwj1pERNCFDrrIsvOySMVrkuueJvBZRsL8+J/d3Lrl2vt5QPeXsp7C/ZyvoDLwERVcBxT9PJVRtfibsug/daXeM8/ZWWbIXr/96V/QfD1Ccms3Z/MxP/ttHe1WdNWeJrFGtuwKrd1j3b53dv0aBJVKIPIlVJex+6FmvXNsLRm9pi0yL5ChPO5Dap7HqD/28bDJJ3PCYDeW7CHNs/P5cd1BzmbmsEbZgqKB/rGEBIcRP1qjtdKTnEcH7l74lAaVi/vMMZLa3hw6l8Ox/VqEkXnhlVZ+Hg/nr+iNdPH9LKX2zg/L2/P30PS+TQysrJ5bfYuh9nDB5NT7NtL95xwWI3gi+XxpGZkcdHHmabCIIGYEKLQ2T6v3I25CfIwWN+Tu7/dQLYlz9fGA6f8utbfiqf789o1bQEY0a4O/+rWkIRJI4gIzV8gEGzJ4H/4VIqXI0u+eyyz/b5emQA4BjHObJnzL2td2+MxgWQLtDKzs/lh7QGm/eUYTDkvLB8eEkxMVHnu6tmIT//VmXdvdJyxa+32+95cAuuLZfG8NmsX83cag+g9Zbl3Dm5sr0d3AaptLGVC0gVWxCU5TJKoXTmChEkj+P6erl7uHBLPpnHz52v4bGk8zZ+dY3/PWd+royavc5h5+vXKBFo8N4eWE+YQPXYms7fl3s0ppGtSCFEERnaoy6YDp3nysuauO5UxkN05ZxcY2e+dE4Eu2p1IzDM5A/knr9jPHW4GZNuyrudVRGgwkWaahWCn7qAfcvnwcscaJPZ6fXGeU3HkZsnficzfeZyqkWH8e3Azr6sJFKYNCckOy0C9MmsXr8za5TWJ6sMDmtC0ZgUub+faJVkcbDxwCoBWE3LWeBzVvSHfrjaCqPUJydzj1I2+6Il+9m3bwuB1Kkdw9EwqcYnn+XTpPm7r1pBmtSqSdP4k8UkXiLesvOBpKS3r+2DlWO/d4ckX0tFa0++tJYBvKztc37mew9qcx8+mssG8f4CFuxNpW7cyl//HMcHtU79t9XjNB37YxPs3dWBkB+8TLso6CcSEEIUuIjSY181ZX86ClJFE9cNFroN9f72/u8sffmcztx3lyg6OY2J2vHiZwxJG+RXutERTT0t3jq8yCjmr/h1fr7dvd29cPV919IfrPl3tttzTLD8wWpyuaO86nqm4WLj7uEtZhGVFhlZ1vHdRHz9rpMewjYG0LQQ/afZuj+d0b+x+dQZbCopeTaKo68M4rONn0+zBlW1WpDdvXt+eN69vz7vz9/D+wr3c+c16h/33Ttng4UzD93d3tef9s3rkp80MaVXbYSUL4Ui6JoUQAaVQaK0dZpW1q2d8wJULC/YtaafTosvlw0PylVXfZlibOtzdqxHjR7TM9zVsmtWqWOBreOKc8iC0GOcq+/2BHoGuQp65a1U9kGR0Lz93eSse6NfYZb/Vle2NlqB33cymdCfulWEex8LZZt12bOC6msDoPjE8O6Ilt3bNaX3s9tpCewvXL/d19+nnAx7XS3X2omXNT4BYy2QK2/vXZudR9ytOCEPxfdcKIcqEoCBj3Il1RtlHt3TiscHNiIkqz38f6sUjA5vy473dgJzp+jYdnJa58TTNPy/CQoJ47vJWHpOO5vVaeemOPHUhnc+XuV+yJul8Glf8ZwXRY2cSPXYmq/Y55qe64bPVpKRnkpaZ5XUGX2GIMJcfuq6z+w/yzg29z3osjp4d0cqlbM6OYwDc3auRx0XtbWzjsXo0zr2V8q6ejbxOHLite0P6Na/BHT2iXfY9M7wl9/SO8dgt7WkShDvOEw7GD3f9Z+SOHtGM6hHNnpeH8erVbdn36nCHMZTOS31d+4n71lJhkEBMCBFQCiN9Ras6xvI1cx7tTf1qkTw8sClKKVrWqcS/Bzeje+PqJEwaQcs6Ocvc1Kkc4bJguKcxNoF2f9/GhPnQYtVx4nxenbWb9xbscdkX+/ICtv2T8yF3++R1gJGawKbVhLk0f3YOg99dVqQLOZc3lyWKqVGeef/u45CZvqGX2YTFWVhIEP2bG/8gFMbC9FadGnpfN7Na+TC+ubML1b0EVd5WsMiLn0Z3s2+HhwYx48GeDvtv7mK0vIWFBHFL1wb2ANCWQqR7THVGuElFItyTQEwIEVAZWdkkX0jHNhEytw+TLMuMyciw4BKTsT4sJIj0rGwSz6bmfjDwnTkg3MbbEjaPDXYzCQKYvd3/s9aOnrnotnyEOeD+vj6NaVarosOKBSX5Q/mjWzvxya2dXLri/OG+PjkD/Z1bN/PDX++F2paZmwt3JdKuXhWH+29e2313+yRztvGka9vy+nXtmPfvPn6pT2kngZgQIqDW7k8m4WSKvaUnt1Yja0bvyLAQFuxKdNj/1FD3QUmg2ab/W3OfObMGmScvpPPGnJxB3cv25iw/4zx2KSRYMdXNjM4J03f4NbXHCzN20P21RXyzcr/LPoXRLWztHtv10lAeHdTU/WzZEiIyLIRhbes4JCq9rHXel8Waem9XHhrQhPmW4OTfg5vZs/E/PMB9AtW88NfEkOio8owd1gKAZrWMVq5RPaJJmDTCazd7bHQ1EiaNoGH18lQID3EYH9qrTBUAABWbSURBVHnyfNG1zpY0EogJIYqFT5ca46Jyy9d1yrKmnrWbbkTbOozq3pA7ezQqnAoW0B5zzNbexPMej3FORvvxkn2kmmkLrAPzJ17Vhp8t3UeZWZoeTaLsLRJWP633PGsxr9buN4LgI2fct+o5N2aWCwvm0UHNvC4zVFK0r18l3+uSAvRoHMXjQ5rTtFZF1j0zkD/H9CQiNJirOtYlYdIIhyz6+TWghVG/3k2NMWkxUeW9rmbgzejeMTx/RSseHdSswPUC6Pyy5yTNZZ0EYkKIYsU5ZYQzW7LVX+93nAm26eApXhzZpthOk5+30zUVgjN3qwK0eG4OP647yE/rDzmUHz6V00U4rI2REPXGS+tTv5pjaoMJ03fkp7punTXH332+LJ6nftvisK9kdBAXTA8ztcTe456DaV/UrBThMsnEHwa3qkXcK8O4pLLxGrind0y+Zw8HBSnu7NmI8uH+z3KVmpHl0PrryZztR/l1w6FcjyvpJBATQpQoN3dpwMqxA7g0uppD+aODCt61U5ieu9x1Bp6zTWYCzeevcDx23B/b7JnXv72rC4BD7jTbh61Syuf0A/nxz+mc4O+XDYcd9mkNJb/dyzvb2KirOhbfBKUhwUH2VBLOaSQCYYmZ4LaL5f3a4rk5NH5mFmdSMjhw0nOy2fu/38STXhLGlhaS0FUIUaz4MvPLXULLro3cJ8IsLu7u1YiJ/9vp9ZiHfjTWCUzzMq4rwmwxDA0OYspdXVzWJPQ2q64gPlvqmlIjeuxMtjw/xJ4ypDR0QXrTo3GU31dGKAzXda5Hv+Y1qVHIMz19ER1VnqgK4TSuWYHosTMd9rV/aR4AW18YQqUIx7QzU9fmdKmPn7aNV6527XYvLaRFTAhRrFSO9D0P2JxHe/Pmde2Y+2gfoqNyzx4eaDUqhtO2rtFKsfPIWU5b1ul77JfN9u3hbVxnGVYMDyG2YVW6xuQEnH2a1aCR031f37ke79zQnrmP9qFJzQo+JcT1xWsessEfMheBPpuaUeAF14V/KKWKRRBmU6lciENrqrPNB0+7lD0zbZt9+4e1B/n72Dmix850uxRaSSeBmBAioNaNH5jvc1vUrsT1sfU9TqcvbprUqEBEaBDTN//D8A+W0+ElY3HmDQnJ/LHpH/txzkk1AW7p2oDffMhOHxEazDWd6tG8dkU6NahCubBgr6kv8sM6Ps821mf65iN+naEpSo+KEaEOK2c4s65paVPF6R+yy95bBsC3qxL8WrfiwOdATCkVrJT6Syn1P/PxQKXUJqXUZqXUCqVUE7M8XCn1s1IqTim1VikVbbnGOLP8b6XUZZbyoWZZnFJqrP9uTwhR3NWwdKX1bFK8uxcLKiwkiPTMbD5bGm8vSzyb6rBO49pnBtqPtcpPotpsDedSM2k0bhbXfbIqn7XGJTGsdXze+bRMZm71f74yUXpsOeTa4mX1wcK93OW0tuXpFPev91insaGlQV5axB4BdlkefwLcqrXuAEwFnjXL7wZOaa2bAO8CrwMopVoBNwGtgaHAx2ZwFwx8BAwDWgE3m8cKIcoA67giVcqHe4eFBHH6YgY7j561lx00u/bAWDi5lplMc/6/+/D1HZfa9yWdz+nG9NVvG3MG1LtrdfCVNT+VcwvmxP/tZMzUTfm+thAAi3Ynuowhcye4FI5D9CkQU0rVA0YAX1qKNWBba6QycMTcHgl8a27/BgxUxl/akcBPWus0rfV+IA7oYn7Faa3jtdbpwE/msUKIMqZ13Uq5H1SChYUEceBkikPZbV+ts2/Xq5ozCaFh9fL0b1GTe3sbedFOXghcQkxb92OvJlHUrGgEilPM2Zu7jxXtmpai5LGtQ2q1e+JQ/n55qEv5Bwv32gOyO3pE89hgxzxmO46cdTmnpPO1Rew94CnAOgDgHmCWUuowcBswySyvCxwC0FpnAmeA6tZy02GzzFO5EKKMeXJIyc3A7gt342QuZuQMPq4Q4TqR/bHBzWlZpxLjhrkuvpwbW9Z2m+ixM0nKR4Zz29I5V1vSNthyalldZUmpIYTNgsf68um/Ojm08IaHBBEeEsyb17VzOPad+TlrrH6zKoH7+zZ22L/1sPduzpIo10BMKXU5kKi13ui069/AcK11PeBr4B3bKW4uo/NR7q4uo5VSG5RSG06c8DzwTwhRMoX4sCh2SRbbsKrX/VFuUk+UCwtm9iO96dIo72NjrupYl+/vdlz6KNYpw/n7C/byxK+OyVkBzqRkMGryOlLSM+0tYtbli4LdzMZ82lwWRwirelUjGdqmDv1b1LSX2YYkXB9bn37mwuruOI+VLI3jEX35q9cTuFIplYDRbThAKTUTaK+1ti2a9jNgm85zGKgPoJQKwei2TLaWm+phdGd6Knehtf5cax2rtY6tUcPzEyeEKHma1qwQ6CoUus5eArFHBhZOQtpeTaP430O9PO5/d8Eeftt4mMysbGZvO2qfYdn+pXks3XOCPm8sYcDbSwE4alnayF3OMOti0UL46sNbOnFNJ9eOsPHDjVZg6xqX59Iy/T4LONByDcS01uO01vW01tEYg+0XYYzhqqyUsnXeDiZnIP8MYJS5fR2wSBu/tRnATeasykZAU2AdsB5oqpRqpJQKM3/GDL/cnRCiRFg/fhB/jukZ6GoUOuf/7m1jwmIbVuXBAU0K7ee2qVuZp4e6tlZZP9CajJ/NAz9souurC4Gc1rmulpa4+TuPef05pT2hqyi4jg1cl3aqEB7CWMvrc+dLl3F/38bc2TPa7TXWJ/g28SQlPZNsH5ZSCrR8ZdbXWmcqpe4FfldKZQOngLvM3V8B3yml4jBawm4yz9mhlPoF2AlkAmO01lkASqkHgblAMDBZa+2/xdGEEMVecUo+WZRscdA7N3QgtJC7ZR/o15j/bT3isMbflsNnXI5LPJfmMHtt5racrqAf7unmcOzb17fncbNbc+Ozg/xdZVEK/XhvN1LSXZOyViqXkzcsMiyEsV66uVMzck/qmpGVTasJcwGK/WoIeXrna62XaK0vN7enaa3baq3ba637aa3jzfJUrfX1WusmWusutnJz3yta68Za6+Za69mW8lla62bmvlf8dXNCCFGcvDorJzv9n2N62lukgoOLpiWpYfVIh1QUV320Mk/nOy+ofm1nY13LulXKFdrSSqJ0iQgNplr5MJfy8JDcw5HfzYTGzoHY1LUHiR47k4uWAO/5GTntOV8uj6c4K90jY4UQohiqGB5Ch/pV6NkkCoAKYUWz7G9wUBDZ2uiSHD1lQ57OdZdqAGD5U/2Z9XBvf1RPlGG+dGtXCDfeJ5lO3Y225ZD2JxkLiJ+5mOGwVuXLM3exeHeiv6rqd7LotxBCFJGhrWszZ8cxfhxtdPG9fHUbHujXOE/raxZEsDJygn2wMI55O4/n6dzwkGC35c6LjgtRWELMlmNrq67V8A+WU6NiuMtKEAB3frOehY/3pXGN4jcpSFrEhBCiiLx+bTsmXdOWNubC3+EhwcQU4QdDcFAQWdmaJXscWweeGe46HueP/8tZ13LBY30LvW5C/PXcYP56brDH/aFBRsiyL/E84/7Yyo4jrmMc3QVhNscts36LE2kRE0KIIlI5MpSbujQI2M8PCVJkZmfz10EjKeYjA5tSJTKU27o15K25e3hkUFOubH8Jf/71D3Uq56SiaOhmEXIh/K2qm7FjVrYWsQ8WxQHw47pDeRqIb50QUJxIICaEEGVEUJDi+NmcFoP7+za2D8Df88owe/lDA5uSYI63AQp9RqcQvghxM6nlopsZmFZLnujH2v0nefr3bexPusDl/1nBE0Oa8X/9mhDkJilxIMi7Swghyojt/zh25bj7YLNpWD2SAS1qMs3SRSlEINm6Jq2+WZVg364UEcJDA5rw6CAjOfJ7N3YgOqo8F9KMYO2hH/8C4K15e+j71uLCr7CPpEVMCCHKiG1OgZi3li6lFJMtawMKEWiR4a4TRl6fY6SE6d00iu8sy3k9OihnsfBjZ13Hhh1KvkhWtna7VFdRkxYxIYQog/ZauiKFKAmsM3dHtK3jsO+OHtEez7utW0O35cfOprJ630mW7w3s2tUSiAkhRBkz4fJWMu5LlGiXRjuu25qW6T6lBUBkmPvUK8fOXOTmL9Zw21frSPdyfmGTd6IQQpQRb1zbDoAulvUjhShJ9r82nP2vDSci1DG48paZv3qFcMYOa8HSJ/uRMGkEU+8xujCv/WS1/ZjEc4FLbSFjxIQQooy4PrYe/VvULLNre4qSz5aB3zkQi432/s/F/X0b27dPnHfMNfbIwKbUqxq4FC3SIiaEEGWEUkqCMFEqWFvAOjWoQuU85AhrXruiw2PbLMtAkUBMCCGEECWKtUXspkvzliS5WU3HQMyXdS4Lk3RNCiGEEKJEsY7pmr39KDdcWt/nc4OCFH89N5j4pPO0q1elMKqXJxKICSGEEKJEOXkh3b79zg0d8nx+1fJhdC5fPCatSNekEEIIIUqUazrWs2/ntkZlcSeBmBBCCCFKFG/pKkqa0nMnQgghhCgTQiUQE0IIIYQIjJBisEakv/gciCmlgpVSfyml/mc+VkqpV5RSe5RSu5RSD1vKP1BKxSmltiqlOlmuMUoptdf8GmUp76yU2mae84EK9FxSIYQQQhRb4SFBjOxwCVPv7Zr7wcVcXmZNPgLsAiqZj+8A6gMttNbZSqmaZvkwoKn51RX4BOiqlKoGPA/EAhrYqJSaobU+ZR4zGlgDzAKGArMLcF9CCCGEKKWUUrx/U8dAV8MvfGoRU0rVA0YAX1qKHwBe0lpnA2itE83ykcAUbVgDVFFK1QEuA+ZrrZPN4Gs+MNTcV0lrvVprrYEpwFX+uDkhhBBCiOLM167J94CnAOvy5I2BG5VSG5RSs5VStjUC6gKHLMcdNsu8lR92Uy6EEEIIUarlGogppS4HErXWG512hQOpWutY4Atgsu0UN5fR+Sh3V5fRZuC34cSJE7lVXQghhBCiWPOlRawncKVSKgH4CRiglPoeo+Xqd/OYaUA7c/swxtgxm3rAkVzK67kpd6G1/lxrHau1jq1Ro4YPVRdCCCGEKL5yDcS01uO01vW01tHATcAirfW/gD+BAeZhfYE95vYM4HZz9mQ34IzW+igwFxiilKqqlKoKDAHmmvvOKaW6mbMlbwem+/EehRBCCCGKpYKsNTkJ+EEp9W/gPHCPWT4LGA7EASnAnQBa62Sl1ERgvXncS1rrZHP7AeAboBzGbMlcZ0xu3LgxSSl1oAD1L2pRQFKgKxEAct9li9x32SL3XbbIfRdMQ3eFypioKAqbUmqDOZ6uTJH7LlvkvssWue+yRe67cEhmfSGEEEKIAJFATAghhBAiQCQQKzqfB7oCASL3XbbIfZctct9li9x3IZAxYkIIIYQQASItYkIIIYQQASKBWD4ppeorpRYrpXYppXYopR4xy19QSv2jlNpsfg23nDNOKRWnlPpbKXWZpXyoWRanlBobiPvJC6VUglJqm3l/G8yyakqp+Uqpveb3qma5Ukp9YN7bVqVUJ8t1RpnH71VKjQrU/fhCKdXc8pxuVkqdVUo9Whqfb6XUZKVUolJqu6XMb8+vUqqz+fqJM891t7pGkfNw328qpXab9zZNKVXFLI9WSl20PO+fWs5xe3+efoeB5uG+/fa6Vko1UkqtNe/7Z6VUWNHdnWce7vtnyz0nKKU2m+Wl6fn29NlVqt/jXu478O9xrbV85eMLqAN0MrcrYiS0bQW8ADzh5vhWwBaMpaEaAfuAYPNrHxADhJnHtAr0/eVy7wlAlFPZG8BYc3ss8Lq5PRwjL5wCugFrzfJqQLz5vaq5XTXQ9+bj/QcDxzBywpS65xvoA3QCthfG8wusA7qb58wGhgX6nr3c9xAgxNx+3XLf0dbjnK7j9v48/Q4D/eXhvv32ugZ+AW4ytz8FHgj0PXu6b6f9bwMTSuHz7emzq1S/x73cd8Df49Iilk9a66Na603m9jlgF94XKx8J/KS1TtNa78dIeNvF/IrTWsdrrdMxlpEaWbi1LxQjgW/N7W+BqyzlU7RhDVBFKVUHuAyYr7VO1lqfAuYDQ4u60vk0ENintfaWULjEPt9a62VAslOxX55fc18lrfVqbfy1mmK5VkC5u2+t9Tytdab5cA2Oy7G5yOX+PP0OA8rD8+1Jnl7XZkvBAOA38/wScd9mvW8AfvR2jRL6fHv67CrV73FP910c3uMSiPmBUioa6AisNYseNJs5J1uaJusChyynHTbLPJUXZxqYp5TaqJQabZbV0sZyVZjfa5rlpem+bW7C8Q90aX++wX/Pb11z27m8JLgLx1U/Giml/lJKLVVK9TbLvN2fp99hceWP13V14LTlg66kPN+9geNa672WslL3fDt9dpWZ97ibz2ybgLzHJRArIKVUBYzFzx/VWp8FPgEaAx2AoxjN22A0YTrTXsqLs55a607AMGCMUqqPl2NL031jjm+5EvjVLCoLz7c3eb3PEnn/SqnxQCbwg1l0FGigte4IPAZMVUpVooTenxv+el2X1N/HzTj+s1Xqnm83n10eD3VTVmKfc0/3Hcj3uARiBaCUCsV4Qn/QWv8BoLU+rrXO0lpnA19gNNmDETXXt5xeDzjipbzY0lofMb8nAtMw7vG42WRra7pNNA8vNfdtGgZs0lofh7LxfJv89fwexrHpv9jfvzkI+XLgVrMrArNr7qS5vRFjfFQzvN+fp99hsePH13USRldWiFN5sWXW9RrgZ1tZaXu+3X12UQbe4x7uO+DvcQnE8skcQ/AVsEtr/Y6lvI7lsKsB24ycGcBNSqlwpVQjoCnGgL/1QFNlzCwKw+j2mlEU95AfSqnySqmKtm2MgY7bMepsmzUzCphubs8Abjdn3nQDzphNtnOBIUqpqma3xxCzrLhz+E+5tD/fFn55fs1955RS3cz30O2WaxU7SqmhwNPAlVrrFEt5DaVUsLkdg/H8xudyf55+h8WOv17X5ofaYuA68/xifd+mQcBurbW9+6k0Pd+ePrso5e9xL5/ZgX+P62Iwi6MkfgG9MJojtwKbza/hwHfANrN8BlDHcs54jKj6byyzSMzz9pj7xgf63nK57xiMGVFbgB22+mKMBVkI7DW/VzPLFfCReW/bgFjLte7CGOwbB9wZ6Hvz4d4jgZNAZUtZqXu+MQLNo0AGxn9/d/vz+QViMT7Y9wEfYiaWDvSXh/uOwxgHY3uPf2oee635+t8CbAKuyO3+PP0OA/3l4b799ro2/2asM3+XvwLhgb5nT/dtln8D3O90bGl6vj19dpXq97iX+w74e1wy6wshhBBCBIh0TQohhBBCBIgEYkIIIYQQASKBmBBCCCFEgEggJoQQQggRIBKICSGEEEIEiARiQgghhBABIoGYEEIIIUSASCAmhBBCCBEg/w8vTfkGhM3XZQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "plt.subplot(2, 1, 1) # \n",
    "plt.plot(df['SHFE.cu1901.close'])\n",
    "# plt.title('SHFE.cu1901.close')\n",
    "plt.subplot(2, 1, 2) # , figsize=(8,3)\n",
    "plt.plot(df['SHFE.cu1902.close'])\n",
    "# plt.title('SHFE.cu1902.close')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1cf18dcba58>]"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "plt.subplot(2, 1, 1) # \n",
    "plt.plot(np.diff(df['SHFE.cu1901.close']))\n",
    "# plt.title('SHFE.cu1901.close')\n",
    "plt.subplot(2, 1, 2) # , figsize=(8,3)\n",
    "plt.plot(np.diff(df['SHFE.cu1902.close']))\n",
    "# plt.title('SHFE.cu1902.close')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['diff'] = df['SHFE.cu1901.close'] - df['SHFE.cu1902.close']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,3))\n",
    "plt.plot(df['diff'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6.922455057721147e-17"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# ts.adfuller(np.diff(df['SHFE.cu1901.close'][1:1000]),1)[1]\n",
    "coint(df['SHFE.cu1901.close'][1:1000], df['SHFE.cu1902.close'][1:1000])[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 协整检验的函数\n",
    "def cointegration_test(series01, series02):\n",
    "    p1 = ts.adfuller(series01, 1)[1]\n",
    "    p2 = ts.adfuller(series01, 1)[1]\n",
    "    # 同时平稳或不平稳则差分再次检验\n",
    "    if (p1 > 0.1 and p2 > 0.1) or (p1 < 0.1 and p2 < 0.1):\n",
    "        p1_diff = ts.adfuller(np.diff(series01), 1)[1]\n",
    "        p2_diff = ts.adfuller(np.diff(series02), 1)[1]\n",
    "        # 同时差分平稳进行OLS回归的残差平稳检验\n",
    "        if p1_diff < 0.1 and p2_diff < 0.1:\n",
    "            \n",
    "            if coint(series01, series02)[1] > 0.1:\n",
    "                result = False\n",
    "            else:\n",
    "                result = True\n",
    "            return result\n",
    "        else:\n",
    "            return False\n",
    "    else:\n",
    "        return False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "result = cointegration_test(np.array(df['SHFE.cu1901.close']), np.array(df['SHFE.cu1902.close']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "# mean = np.mean(df['diff'])\n",
    "up = np.percentile(df['diff'],75)\n",
    "up_limit =np.percentile(df['diff'],95)\n",
    "down = np.percentile(df['diff'],25)\n",
    "down_limit = np.percentile(df['diff'],5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
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     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
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   "execution_count": 68,
   "metadata": {},
   "outputs": [
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     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
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   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
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     "execution_count": 69,
     "metadata": {},
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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